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All sources NASA NTRS DOE OSTI

DOE OSTI2020

SO(3)-invariance of informed-graph-based deep neural network for anisotropic elastoplastic materials

This work examines the frame-invariance (and the lack thereof) exhibited in simulated anisotropic elasto-plastic responses generated from supervised machine learning of classical multi-layer and informed-graph-based neural networks, and proposes different remedies to fix this drawback. The inherent hierarchical relations among physical quantities and state variables in an elasto-plasticity model are first represented as informed, directed graphs, where three variations of the graph are tested. While feed-forward neural networks are used to train path-independent constitutive relations (e.g., elasticity), recurrent neural networks are used to replicate responses that depends on the deformation history, i.e. or path dependent. In dealing with the objectivity deficiency, we use the spectral form to represent tensors and, subsequently, three metrics, the Euclidean distance between the Euler Angles, the distance from the identity matrix, and geodesic on the unit sphere in Lie algebra, can be employed to constitute objective functions for the supervised machine learning. In this, the aim is to minimize the measured distance between the true and the predicted 3D rotation entities. Following this, we conduct numerical experiments on how these metrics, which are theoretically equivalent, may lead to differences in the efficiency of the supervised machine learning as well as the accuracy and robustness of the resultant models. Neural network models trained with tensors represented in component form for a given Cartesian coordinate system are used as a benchmark. Our numerical tests show that, even given the same amount of information and data, the quality of the anisotropic elasto-plasticity model is highly sensitive to the way tensors are represented and measured. The results reveal that using a loss function based on geodesic on the unit sphere in Lie algebra together with an informed, directed graph yield significantly more accurate rotation prediction than the other tested approaches.

42 ENGINEERING↗

DOE OSTI2020

Spectroscopic signatures of next-nearest-neighbor hopping in the charge and spin dynamics of doped one-dimensional antiferromagnets

In this work, we study the impact of next-nearest-neighbor (nnn) hopping on the low-energy collective excitations of strongly correlated doped antiferromagnetic cuprate spin chains. Specifically, we use exact diagonalization and the density matrix renormalization group method to study the single-particle spectral function, the dynamical spin and charge structure factors, and the Cu L-edge resonant inelastic x-ray scattering (RIXS) intensity of the doped t-t'-J model for a set of t' values. We find evidence for the breakdown of spin-charge separation as |t'| increases and identify its fingerprints in the dynamical response functions. The inclusion of nnn hopping couples the spinon and holon excitations, resulting in the formation of a spin-polaron, where a ferromagnetic spin polarization cloud dresses the doped carrier. The spin-polaron manifests itself as additional spectral weight in the dynamical correlation functions, which appear simultaneously in the spin- and charge-sensitive channels. We also demonstrate that RIXS can provide a unique view of the spin-polaron, due to its sensitivity to both the spin and charge degrees of freedom.

1D spin chains↗

DOE OSTI2024

Effects of noise on the overparametrization of quantum neural networks

Overparametrization is one of the most surprising and notorious phenomena in machine learning. Recently, there have been several efforts to study if, and how, quantum neural networks (QNNs) acting in the absence of hardware noise can be overparametrized. In particular, it has been proposed that a QNN can be defined as overparametrized if it has enough parameters to explore all available directions in state space. That is, if the rank of the quantum Fisher information matrix (QFIM) for the QNN's output state is saturated. Here, we explore how the presence of noise affects the overparametrization phenomenon. Our results show that noise can “turn on” previously zero eigenvalues of the QFIM. This enables the parametrized state to explore directions that were otherwise inaccessible, thus potentially turning an overparametrized QNN into an underparametrized one. For small noise levels, the QNN is quasioverparametrized, as large eigenvalues coexists with small ones. Then, we prove that as the magnitude of noise increases all the eigenvalues of the QFIM become exponentially suppressed, indicating that the state becomes insensitive to any change in the parameters. As such, there is a pull-and-tug effect where noise can enable new directions but also suppress the sensitivity to parameter updates. Finally, our results imply that current QNN capacity measures are ill-defined when hardware noise is present. Published by the American Physical Society 2024

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Observations of ozone, acyl peroxy nitrates, and their precursors during summer 2019 at Carlsbad Caverns National Park, New Mexico

Carlsbad Caverns National Park (CAVE) is located in southeastern New Mexico and is adjacent to the Permian Basin, one of the most productive oil and natural gas (O&G) production regions in the United States. Since 2018, ozone (O 3 ) at CAVE has frequently exceeded the 70 ppbv 8-hour National Ambient Air Quality Standard. We examine the influence of regional emissions on O 3 formation using observations of O 3 , nitrogen oxides (NO x = NO + NO 2 ), a suite of volatile organic compounds (VOCs), peroxyacetyl nitrate (PAN), and peroxypropionyl nitrate (PPN). Elevated O 3 and its precursors are observed when the wind is from the southeast, the direction of the Permian Basin. We identify 13 days during the July 25 to September 5, 2019 study period when the maximum daily 8-hour average (MDA8) O 3 exceeded 65 ppbv; MDA8 O 3 exceeded 70 ppbv on 5 of these days. The results of a positive matrix factorization (PMF) analysis are used to identify and attribute source contributions of VOCs and NO x . On days when the winds are from the southeast, there are larger contributions from factors associated with primary O&G emissions; and, on high O 3 days, there is more contribution from factors associated with secondary photochemical processing of O&G emissions. The observed ratio of VOCs to NO x is consistently high throughout the study period, consistent with NO x -limited O 3 production. Finally, all high O 3 days coincide with elevated acyl peroxy nitrate abundances with PPN to PAN ratios > 0.15 ppbv ppbv -1 indicating that anthropogenic VOC precursors, and often alkanes specifically, dominate the photochemistry. Implications: The results above strongly indicate NO x -sensitive photochemistry at Carlsbad Caverns National Park indicating that reductions in NO x emissions should drive reductions in O 3 . However, the NO x -sensitivity is largely driven by emissions of NO x into a VOC-rich environment, and a high PPN:PAN ratio and its relationship to O 3 indicate substantial influence from alkanes in the regional photochemistry. Thus, simultaneous reductions in emissions of NO x and non-methane VOCs from the oil and gas sector should be considered for reducing O 3 at Carlsbad Caverns National Park. Reductions in non-methane VOCs will have the added benefit of reducing formation of other secondary pollutants and air toxics.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

The Timepix4 analog front-end design: Lessons learnt on fundamental limits to noise and time resolution in highly segmented hybrid pixel detectors

This manuscript describes the optimization of the front-end readout electronics for high granularity hybrid pixel detectors. The theoretical study aims at minimizing the noise and jitter. The model presented here is validated with both circuit post layout simulations and measurements on the Timepix4 Application Specific Integrated Circuit (ASIC). The analog front-end circuit and the procedure to optimize the dimensions of the main transistors are described with detail. The Timepix4 is the most recent ASIC designed in the framework of the Medipix4 Collaboration. It was manufactured in 65nm CMOS process, and consists of a four side buttable matrix of 448 × 512 pixels with 55µm pitch. The analog front-end has a gain of ~36mV/ke - when configured in High Gain Mode, and ~20mV/ke - when configured in Low Gain Mode. The Equivalent Noise Charge (ENC) is ~68e - rms and ~80e - rms in High Gain Mode and in Low Gain Mode respectively. In event driven mode the incoming hits can be time stamped within a ~ 200ps time bin and the chip can deal with a maximum flux of ~ 3.6MHzmm –2 s –1 . In photon counting mode, the chip can deal with up to ~ 5GHzmm –2 s –1 . The routine designed to optimize the Timepix4 front-end is then used to analyze the performance limits in terms of jitter and noise for Charge Sensitive Amplifiers in pixel detectors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Prediction of curing kinetics of resorcinol‐added resole phenolic resins using differential scanning calorimetry for the fabrication of carbon/carbon composites

Phenolic resins are commonly used as carbon precursors for the fabrication of carbon/carbon composites due to their high carbon yield and aromatic nature. To decrease curing times, acid catalysts are generally used, but the addition of resorcinol was found to have a similar effect while being incorporated into the resin matrix with no contamination or corrosion issues. In this work, the curing kinetics of pure, 10, 20, and 30 wt% resorcinol-added phenolic resins were investigated through differential scanning calorimetry. Heating rates of 0.5, 1, 2.5, and 5°C min -1 were used with several curing models to predict isothermal curing. Averaged mean absolute error (MAE) for the isoconversional mathematical approaches namely Kissinger–Akahira–Sunose (MAE = 12.9 min), Flynn–Wall–Ozawa (15.8 min), and Vyazovkin (14 min) show that these methods provide the best predictions, attributed to their adoption of an activation energy that depends on the extent of cure (E a (α)). The Kissinger method (MAE = 36 min), which depends only on peak temperature with a constant activation energy assumption, and the data noise sensitive Friedman model (MAE = 1144.7 min) provide the least accurate results. Thermogravimetric analysis revealed that resorcinol decreases the curing times by up to 71% without lowering carbon yield.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Ionizing radiation effects in SONOS-based neuromorphic inference accelerators

Here, we evaluate the sensitivity of neuromorphic inference accelerators based on Silicon-Oxide-Nitride-Oxide-Silicon (SONOS) charge trap memory arrays to total ionizing dose (TID) effects. Data retention statistics were collected for 16 Mbit of 40 nm SONOS digital memory exposed to ionizing radiation from a Co-60 source, showing good retention of the bits up to the maximum dose of 500 krad(Si). Using this data, we formulate a rate-equation-based model for the TID response of trapped charge carriers in the ONO stack, and predict the effect of TID on intermediate device states between ‘program’ and ‘erase’. This model is then used to simulate arrays of low-power, analog SONOS devices that store 8-bit neural network weights and support in situ matrix-vector multiplication. We evaluate the accuracy of the irradiated SONOS-based inference accelerator on two image recognition tasks – CIFAR-10 and the challenging ImageNet dataset – using state-of-the-art convolutional neural networks, such as ResNet-50. We find that across the datasets and neural networks evaluated, the accelerator tolerates a maximum TID between 10 krad(Si) and 100 krad(Si), with deeper networks being more susceptible to accuracy losses due to TID.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Quantum embedding study of strain- and electric-field-induced Stark effects on the NV - center in diamond

The NV - color center in diamond has been demonstrated as a powerful nanosensor for quantum metrology due to the sensitivity of its optical and spin properties to external electric, magnetic, and strain fields. In view of these applications, we use quantum embedding to derive a many-body description of strain- and electric-field-induced Stark effects on the NV - center. Here, we quantify how strain longitudinal to the axis of NV - shifts the excited states in energy, while strain with a component transverse to the NV - axis splits the degeneracies of the 3 E and 1 E states. The largest effects are for the optically relevant 3 E manifold, which splits into E x and E y with transverse strain. From these responses we extract strain susceptibilities for the E x/y states within the quasilinear regime. Additionally, we study the many-body dipole matrix elements of the NV - and find a permanent dipole 1.6 D at zero strain, which is somewhat smaller than that obtained from recent density functional theory calculations. We also determine the transition dipole between the E x and E y and how it evolves with strain.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Absolute cross section of the C 12 ( p , γ ) N 13 reaction

Solar neutrino measurements have recently reached a level of sensitivity such that CNO fluxes can now be experimentally determined. While these first measurements are still only sensitive to the higher energy neutrinos resulting from the β + decays of 15 Ο produced by the 14 Ν ⁡( p ,$\gamma$)⁢ 15 O reaction, future measurements will work towards detection of neutrinos from the β + decay of 13 N from the 12 C ⁡( p ,$\gamma$)⁢ 13 N reaction. Here, this paper reports on a recent measurement of the 12 C ⁡( p ,$\gamma$)⁢ 13 N reaction covering a broad laboratory energy range between 1.0 and 2.5 MeV. The measurement was made to better determine the overall normalization of the absolute cross section and to explore the interference effects between the two broad, overlapping resonances at proton energies of 0.460 and 1.689 MeV and the direct capture to the ground state of 13 N in the framework of a multichannel R -matrix analysis. This work takes into account previous radiative capture as well as elastic 12 C ( p , p ) 12 C scattering data, making uncertainty estimations using a Bayesian framework, to determine a reliable extrapolation of the low energy S factor towards the stellar energy range of CNO hydrogen burning. These new experimental results, and a detailed investigation of the past literature data, suggest that the resonant component of the cross section should be 30% lower than previously accepted.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

Mapping the proteogenomic landscape enables prediction of drug response in acute myeloid leukemia

Acute myeloid leukemia is a poor prognosis cancer commonly stratified by genetic aberrations, but these mutations are often heterogeneous and don’t always predict therapeutic response. Here we combine transcriptomic, proteomic, and phosphoproteomic datasets with ex vivo drug sensitivity data to help understand the underlying pathophysiology of AML beyond mutations. We measured the proteome and phosphoproteome of 210 patients and combined them with genomics and transcriptomic measurements to identify four proteogenomic subtypes that complemented existing genetic subtypes. We then built a predictor to classify samples into subtypes based on 147 molecular features and mapped them to a ‘landscape’. Each region of this landscape corresponded to specific drug response patterns. We then built a drug response prediction model to identify drugs that target distinct subtypes. We can ultimately use these models to predict drug treatment response and prioritize treatments. Finally, we extended our models and mapped a series of cell lines representing various stages of quizartinib resistance into our subtype landscape, predicting and experimentally validating a switch in sensitivity to venetoclax to panobinostat, two drugs with very different mechanisms than quizartinib. Our results show how multi-omics data together with drug sensitivity data can inform therapy stratification and drug combinations in AML.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Photoluminescence Probes Ion Insertion into Amorphous and Crystalline Regions of Organic Mixed Conductors

Abstract Organic mixed ionic‐electronic conductors (OMIECs) have emerged as promising materials for a wide range of next‐generation technologies, including bioelectronics and neuromorphic computing. The performance of these materials depends on the transport of ions through the polycrystalline polymer matrix as well as how the distribution of ions and polarons in crystalline and amorphous regions impacts electronic transport. However, it is often challenging to distinguish whether ions enter crystalline or amorphous regions. In this work, steady‐state and time‐resolved photoluminescence (PL) spectroelectrochemistry is used to probe initial ion insertion in crystalline and amorphous regions of the OMIEC material poly(3‐[2‐[2‐(2‐methoxyethoxy)ethoxy]ethyl]thiophene ‐2,5‐diyl) (P3MEEET) as a function of applied voltage. It is found that PL spectroelectrochemistry reports on the initial stages of electrochemical doping through the quenching of PL emission. By distinguishing between amorphous and crystalline contributions to the PL spectrum, ion insertion in crystalline and amorphous regions as a function of voltage is tracked. It is found that PL spectroelectrochemistry is much more sensitive to the initial injection of ions than complementary methods, highlighting its potential as a sensitive tool for interrogating ion injection in OMIECs.

Collins, Garrett W.↗

DOE OSTI2021

Origin and resummation of threshold logarithms in the lattice QCD calculations of PDFs

Many present lattice QCD approaches to calculate the parton distribution functions (PDFs) rely on a factorization formula or effective theory expansion of certain Euclidean matrix elements in boosted hadron states. In the quasi- and pseudo-PDF methods, the matching coefficient in the factorization or expansion formula includes large logarithms near the threshold, which arise from the subtle interplay of collinear and soft divergences of an underlying 3D momentum distribution. We use the standard prescription to resum such logarithms in the Mellin-moment space at next-to-leading logarithmic accuracy, which also accounts for the Dokshitzer-Gribov-Lipatov-Altarelli-Parisi evolution, and we show that it can suppress the PDF at large x . Unlike the deep inelastic scattering and Drell-Yan cross sections, the resummation formula is away from the Landau pole. We then apply our formulation to reanalyze the recent lattice results for the pion valence PDF, and find that within the current data sensitivity, the effect of threshold resummation is marginal for the accessible moments and the PDF at large x.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Multi-channel front-end ASIC for a 3D position-sensitive detector

Arrays of 3D position-sensitive detectors (3DPSD), operating at room temperature and using cadmium zinc telluride (CZT) and thallium bromide (TIBr) sensors, are suitable for gamma-ray spectrometry in many applications. One detector configuration, the 3D position-sensitive Virtual Frisch-Grid detector (VFG), is particularly advantageous for integrating into large area arrays. The signals generated inside each detector of the array are captured with the anode, cathode and four pads that enable the reconstruction of the position and energy of the ionizing interaction by measurements of amplitude and timing of the signals. For these applications, a low-noise front-end ASIC has been developed, capable of processing bipolar signals (needed because of AC-coupling of certain electrodes). The ASIC can be coupled to an ADC in order to form a compound “waveform digitizer” capable of post-processing the analog signals and determining amplitude and timing information. This paper describes a 32-channel front-end ASIC that is suitable for reading out a 3 × 3 or 4 × 4 element matrix in the VFG configuration. Each channel is composed of a low-noise charge amplifier with an adaptive continuous reset feedback circuit suitable for both positive and negative charge, a first order shaper and a single-to-differential converter output stage. Voltage and current references are all internally generated by 10-bit DACs and the chip is fully controllable with the I 2 C communication protocol. The readout channel response has been verified using the implemented injection circuit. Linear behavior up to ~75 ke ± with the gain of ~80 mV/fC, and up to ~200 ke ± with the gain of ~30 mV/fC was demonstrated. In conclusion, the first test result waveforms using a 137 Cs radioactive source on a 5 × 5 × 12 mm 3 TIBr crystal are reported.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Optimal 1D Ly α forest power spectrum estimation – I. DESI-lite spectra

ABSTRACT The 1D Ly α forest flux power spectrum P1D is sensitive to scales smaller than a typical galaxy survey, and hence ties to the intergalactic medium’s thermal state, suppression from neutrino masses, and new dark matter models. It has emerged as a competitive framework to study new physics, but also has come with various challenges and systematic errors in analysis. In this work, we revisit the optimal quadratic estimator for P1D, which is robust against the relevant problems such as pixel masking, time evolution within spectrum, and quasar continuum errors. We further improve the estimator by introducing a fiducial power spectrum, which enables us to extract more information by alleviating the discreteness of band powers. We meticulously apply our method to synthetic Dark Energy Spectroscopic Instrument (DESI) spectra and demonstrate how the estimator overcomes each challenge. We further apply an optimization scheme that approximates the Fisher matrix to three elements per row and reduces computation time by 60 per cent. We show that we can achieve per cent precision in P1D with 5-yr DESI data in the absence of systematics and provide forecasts for different spectral qualities.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Correlations Between Panoramic Imagery and Gamma-Ray Background in an Urban Area

When searching for radiological sources in an urban area, a vehicle-borne detector system will often measure complex, varying backgrounds primarily from natural gamma-ray sources. Much work has been focused on developing spectral algorithms that retain sensitivity and minimize the false-positive rate even in the presence of such spectral and temporal variability. However, information about the environment surrounding the detector system might also provide useful clues about the expected background, which if incorporated into an algorithm, could improve performance. Recent work has focused on extensive measuring and modeling of urban areas with the goal of understanding how these complex backgrounds arise. This work presents an analysis of panoramic video images and gamma-ray background data collected in Oakland, California, by the radiological multisensor analysis platform (RadMAP) vehicle. Features were extracted from the panoramic images by semantically labeling the images and then convolving the labeled regions with the detector response. A linear model was used to relate the image-derived features to gamma-ray spectral features obtained using nonnegative matrix factorization (NMF) under different regularizations. Here we find some gamma-ray background features correlate strongly with image-derived features that measure the response-adjusted solid angle subtended by sky and buildings, and we discuss the implications for the development of future, contextually aware detection algorithms.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Two-color, intracavity pump–probe, cavity ringdown spectroscopy

Here, we report a proof-of-principle demonstration of intracavity pump–probe, cavity ringdown (CRD) detection in a three-mirror, traveling-wave cavity. With cavity-enhanced pump power and probe absorption path length, the technique is a generally applicable, high-sensitivity, high-selectivity detection method. In our experiments, the pump radiation is switched off during every other probe ringdown, which allows uncorrelated measurements of analyte and background cavity decay rates. The net, two-color signal from the difference between the pump-on and pump-off decay rates is immune to empty-CRD drifts and spectral overlaps from non-target molecular transitions. The immunity to the ringdown drifts allows longer signal-averaging and, thus, higher detection sensitivity. The ability to compensate for the background absorption enhances the detection selectivity in spectrally congested regions. Our technique is well-suited for trace-detection in the mid-IR region, where pump–probe schemes based on strong rovibrational transitions can be applied. In this work, two-color CRD detection is implemented on a ladder-type, three-level system based on the N 2 O, ν 3 = 1 ← 0, P(19) (pump) and ν 3 = 2 ← 1, R(18) (probe), rovibrational transitions. By frequency-locking two-quantum cascade lasers to the p-polarization (pump, Finesse = 5280) and s-polarization (probe, Finesse = 67 700) cavity modes, we achieve high intracavity pump power (36 W) and high probe ringdown rates (>2 kHz). The observed two-color spectra are simulated by a density-matrix, three-level system model that is solved under the constraints of the cavity resonance conditions. In addition to its background compensation capability, experimental flexibility in the selection of pump–probe schemes and signal insensitivity to intracavity laser power are further features that enhance the utility of our technique for mid-IR trace-detection.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Mechanical and Thermophysical Properties of 3D-Printed SiC-FY20

In the Transformational Challenge Reactor (TCR), the fuel blocks consist of an additively-manufactured silicon carbide (SiC) matrix and uranium nitride tristructural isotropic (UN TRISO) fuel particles, which are stacked to form fuel columns. The SiC matrix is manufactured using binderjet 3D printing followed by loading the TRISO fuel particles and the chemical vapor infiltration (CVI) process. Because the fuel matrix is a primary component of the TCR core and its response to mechanical and thermal loads during operation is one of the most influential factors on the integrity of TCR core, testing and evaluation have focused on producing mechanical and thermophysical properties data for the binderjet/CVI SiC. Mechanical and thermophysical properties were measured from various types of specimens printed for two or three orientations, which included equibiaxial flexural failure strength, elastic constants, thermal diffusivity and conductivity, density, and the coefficient of thermal expansion. Flexural failure strength datasets showed similar Weibull distributions regardless of sample variants including different orientations. The mean failure strengths of the 3D-printed SiC variants were in the range of 286–306 MPa, which are 22–27% lower than that of the CVD SiC. Thermophysical test results showed that specific heat and thermal expansion are not sensitive to the build directions of SiC samples, while thermal diffusivity is highly dependent on the build direction and can be correlated to the anisotropic character of the 3D-printed SiC. This report also includes discussions on the uniaxial tensile properties of the as-printed SiC before CVI and on ongoing efforts for irradiation effects studies.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

Mechanical and Thermophysical Properties of 3D-Printed SiC before and after Neutron Irradiation – FY21

This report presents the mechanical and thermophysical properties of 3D-printed SiC before and after neutron irradiation that have been evaluated to assess the fuel matrix material for the Transformational Challenge Reactor (TCR). The TCR fuel form consists of an additively-manufactured silicon carbide (SiC) matrix and uranium nitride tristructural isotropic (UN TRISO) fuel particles, which is manufactured through a newly developed processing route combining binderjet 3D printing, TRISO fuel particle loading, and chemical vapor infiltration (CVI). Because the fuel matrix is a primary component of the TCR core and its response to mechanical and thermal loads during operation is one of the most influential factors on the integrity of TCR core, testing and evaluation have focused on producing mechanical and thermophysical properties data for the binderjet/CVI SiC. Baseline mechanical and thermophysical properties were measured from the disk specimens printed for different and sizes orientations, which included equibiaxial flexural failure strength, elastic constants, thermal diffusivity and conductivity, density, and the coefficient of thermal expansion. Flexural failure strength datasets showed similar Weibull distributions regardless of sample variants including different orientations. The mean failure strengths of the 3D-printed SiC variants were in the range of 280–310 MPa, which are slightly lower than that of the chemical vapor deposition (CVD) SiC. Thermophysical test results showed that specific heat and thermal expansion are not sensitive to the build direction of SiC samples, while thermal conductivity is highly dependent on the build direction and can be correlated to the anisotropic character of the 3D-printed SiC. Neutron irradiation tests were carried out on the 3D-printed 6-mm diameter SiC disk specimens. Irradiation was carried to 2.3 dpa over a temperature range of 360–880°C. No significant degradation in strength was observed in SiC after irradiations in various conditions and with different orientations. Anisotropy that had been observed in the thermal conductivity of 3D-printed SiC prior to irradiation vanished after irradiation as the irradiation defect thermal resistivity accumulated in the material. Electron microscopy of the microstructure after neutron irradiation showed distinct defect morphologies in the heterogenous material, but no evidence for irradiation-induced cracking or degradation in the microstructure was observed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗