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Results for “interpretable models”

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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Towards replacement of animal tests with in vitro assays: a gene expression biomarker predicts in vitro and in vivo estrogen receptor activity

High-throughput transcriptomics (HTTr) has the potential to support efforts to reduce or replace some animal tests. In past studies, we described a computational approach utilizing a gene expression biomarker consisting of 46 genes to predict estrogen receptor (ER) activity after chemical exposure in ER-positive human breast cancer cells including the MCF-7 cell line. We hypothesized that the biomarker model could identify ER activities of chemicals examined by Endocrine Disruptor Screening Program (EDSP) Tier 1 screening assays in which transcript profiles of the same chemicals were examined in MCF-7 cells. For the 62 chemicals examined including 5 chemicals examined in this study using RNA-Seq, the ER biomarker model accuracy was 1) 97% for in vitro reference chemicals, 2) 76–85% for guideline uterotrophic assays, and 3) 87–88% for guideline and nonguideline uterotrophic assays. For the same chemicals, these accuracies were similar or slightly better than those of the ToxCast ER model based on 18 in vitro assays. The performance of the ER biomarker model indicates that HTTr interpreted using the ER biomarker correctly identifies active and inactive ER reference chemicals. Finally, as part of the HTTr screening program the approach could rapidly identify chemicals with potential ER bioactivities for additional screening and testing.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

A cavitation and dynamic void growth model for a general class of strain-softening amorphous materials

In this work, we derive a homogenized framework for cavitation and dynamic void growth in a general class of strain-softening materials with particular emphasis on amorphous materials. Analytic solutions are derived by considering an assemblage of spherical shells subject to dynamic hydrostatic tensile pressure. The isochoric response of the matrix material is captured by a free volume theory based amorphous viscoplasticity model. The framework accounts for the coupled rate-dependent, strain-softening behavior typically exhibited in amorphous materials. Validation of the homogenized theory is carried out against numerous direct numerical simulations with excellent agreement. Furthermore, we find that a reduction in cavitation strength and significant acceleration of dynamic void growth rates is induced as a consequence of strain-softening in the amorphous matrix material. Lastly, the model is utilized to interpret some non-intuitive experimental observations of amorphous materials subject to shock compression and subsequent spall failure.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Interpreting experimental measurements of helium bubbles using stochastic cluster dynamics models of heterogeneous nucleation and growth in irradiated ferritic alloys

Among a number of other advantageous features, ferritic/martensitic steels are being considered as fusion reactor structural materials due to their low intrinsic swelling under irradiation. However, under high-energy neutron irradiation, He produced through (n, α) reactions stabilizes vacancy clusters, which then act as seeds for bubble formation and growth, negating the intrinsic swelling resistance of these alloys. Standard models of irradiation damage accumulation and microstructural evolution consider homogeneous nucleation as the basis for bubble formation and growth. However, this generally does not explain the large bubble densities and sizes observed experimentally under a number of different conditions. Here, we propose a more realistic physical model of bubble nucleation, formation, and growth designed to capture recent experimental measurements of He-bubble formation and evolution during co-implantation of He and Fe ions in model ferritic alloys. We find that experimental results are explained only when the following three features are considered simultaneously: (i) heterogeneous nucleation of He-vacancy bubbles at defect sinks (e.g., dislocations, grain boundaries, and second-phase precipitates), (ii) nucleation and growth of bubbles via the ‘trap mutation’ mechanism (i.e., spontaneous production of Frenkel pairs due to absorption of He atoms), and (iii) transition from a growth-limited, He-stabilized bubble regime to a ‘runaway’ void-type growth scenario. The model is implemented into a stochastic cluster dynamics framework that takes advantage of cluster size grouping methods to accelerate the simulations, allowing us to reach 10 dpa of simulated irradiated dose, and to capture cluster sizes in excess of 20 nm. Further, a careful extrapolation exercise conducted assuming classical nucleation theory leads to excellent agreement with the experimental measurements at 50 dpa of irradiation.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Spatiotemporal measurements of striations in a glow discharge’s positive column using laser-collisional induced fluorescence

Here we have observed the behavior of striations caused by ionization waves propagating in low-pressure helium DC discharges using the non-invasive laser-collision induced fluorescence (LCIF) diagnostic. To achieve this, we developed an analytic fit of collisional radiative model (CRM) predictions to interpret the LCIF data and recover quantitative two-dimensional spatial maps of the electron density, n e , and the ratios of LCIF emission states that can be correlated with T e with the use of accurate distribution functions at localized positions within striated helium discharges at 500 mTorr, 750 mTorr, and 1 Torr. To our knowledge, these are the first spatiotemporal, laser-based, experimental measurements of n e in DC striations. The n e and 447:588 ratio distributions align closely with striation theory. Constriction of the positive column appears to occur with decreased gas pressure, as shown by the radial n e distribution. We identify a transition from a slow ionization wave to a fast ionization wave between 750 mTorr and 1 Torr. These experiments validate our analytic fit of n e , allowing the implementation of an LCIF diagnostic in helium without the need to develop a CRM.

42 ENGINEERING↗
DOE OSTI2023

MHz free electron laser x-ray diffraction and modeling of pulsed laser heated diamond anvil cell

A new diamond anvil cell experimental approach has been implemented at the European x-ray Free Electron Laser, combining pulsed laser heating with MHz x-ray diffraction. In this report we use this setup to determine liquidus temperatures under extreme conditions, based on the determination of time-resolved crystallization. The focus is on a Fe-Si-O ternary system, relevant for planetary cores. This time-resolved diagnostic is complemented by a finite-element model, reproducing temporal temperature profiles measured experimentally using streaked optical pyrometry. This model calculates the temperature and strain fields by including (i) pressure and temperature dependencies of material properties, and (ii) the heat-induced thermal stress, including feedback effect on material parameter variations. Making our model more realistic, these improvements are critical as they give 7000 K temperature differences compared to previous models. Laser intensities are determined by seeking minimal deviation between measured and modeled temperatures. Combining models and streak optical pyrometry data extends temperature determination below detection limit. The presented approach can be used to infer the liquidus temperature by the appearance of SiO 2 diffraction spots. In addition, temperatures obtained by the model agree with crystallization temperatures reported for Fe–Si alloys. Our model reproduces the planetary relevant experimental conditions, providing temperature, pressure, and volume conditions. Those predictions are then used to determine liquidus temperatures at experimental timescales where chemical migration is limited. This synergy of novel time-resolved experiments and finite-element modeling pushes further the interpretation capabilities in diamond anvil cell experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Mapping the structural trends in zinc aluminosilicate glasses

The structure of zinc aluminosilicate glasses with the composition (ZnO) x (Al 2 O 3 ) y (SiO 2 ) 1-x-y , where 0 ≤ x < 1, 0 ≤ y < 1, and x + y < 1, was investigated over a wide composition range by combining neutron and high-energy x-ray diffraction with 27 Al magic angle spinning nuclear magnetic resonance spectroscopy. The results were interpreted using an analytical model for the composition-dependent structure in which the zinc ions do not act as network formers. Four-coordinated aluminum atoms were found to be in the majority for all the investigated glasses, with five-coordinated aluminum atoms as the main minority species. Mean Al–O bond distances of 1.764(5) and 1.855(5) Å were obtained for the four- and five-coordinated aluminum atoms, respectively. The coordination environment of zinc was not observed to be invariant. Instead, it is dependent on whether zinc plays a predominantly network-modifying or charge-compensating role and, therefore, varies systematically with the glass composition. The Zn–O coordination number and bond distance were found to be 4.36(9) and 2.00(1) Å, respectively, for the network-modifying role vs 5.96(10) and 2.08(1) Å, respectively, for the charge-compensating role. The more open coordination environment of the charge-compensator is related to an enhanced probability of zinc finding bridging oxygen atoms as nearest-neighbors, reflecting a change in the connectivity of the glass network comprising four-coordinated silicon and aluminum atoms as the alumina content is increased.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Femtosecond pulse parameter estimation from photoelectron momenta using machine learning

Abstract Deep learning models have provided huge interpretation power for image-like data. Specifically, convolutional neural networks (CNNs) have demonstrated incredible acuity for tasks such as feature extraction or parameter estimation. Here we test CNNs on strong-field ionization photoelectron spectra, training on theoretical data sets to ‘invert’ experimental data. Pulse characterization is used as a ‘testing ground’, specifically we retrieve the laser intensity, where ‘traditional’ measurements typically lead to 20% uncertainty. We report on crucial data augmentation techniques required to successfully train on theoretical data and return consistent results from experiments, including accounting for detector saturation. The same procedure can be repeated to apply CNNs in a range of scenarios for strong-field ionization. Using a predictive uncertainty estimation, reliable laser intensity uncertainties of a few percent can be extracted, which are consistently lower than those given by traditional techniques. Using interpretability methods can reveal parts of the distribution that are most sensitive to laser intensity, which can be directly associated with holographic interferences. The CNNs employed provide an accurate and convenient ways to extract parameters, and represent a novel interpretational tool for strong-field ionization spectra.

Szołdra, Tomasz (ORCID:0000000228970506)↗
DOE OSTI2026

Conformalized-KANs: Uncertainty Quantification with Coverage Guarantees for Kolmogorov-Arnold Networks (KANs) in Scientific Machine Learning

This paper explores uncertainty quantification (UQ) methods in the context of Kolmogorov–Arnold Networks (KANs). We apply an ensemble approach to KANs to obtain a heuristic measure of UQ, enhancing interpretability and robustness in modeling complex functions. Building on this, we introduce Conformalized-KANs, which integrate conformal prediction, a distribution-free UQ technique, with KAN ensembles to generate calibrated prediction intervals with guaranteed coverage.} Extensive numerical experiments are conducted to evaluate the effectiveness of these methods, focusing particularly on the robustness and accuracy of the prediction intervals under various hyperparameter settings. We show that the conformal KAN predictions can be applied to recent extensions of KANs, including Finite Basis KANs (FBKANs) and multifideilty KANs (MFKANs). The results demonstrate the potential of our approaches to significantly improve the reliability and applicability of KANs in scientific machine learning.

• Artificial intelligence (AI) / machine learning ↗
DOE OSTI2020

Photometric classification of Hyper Suprime-Cam transients using machine learning

Abstract The advancement of technology has resulted in a rapid increase in supernova (SN) discoveries. The Subaru/Hyper Suprime-Cam (HSC) transient survey, conducted from fall 2016 through spring 2017, yielded 1824 SN candidates. This gave rise to the need for fast type classification for spectroscopic follow-up and prompted us to develop a machine learning algorithm using a deep neural network with highway layers. This algorithm is trained by actual observed cadence and filter combinations such that we can directly input the observed data array without any interpretation. We tested our model with a dataset from the LSST classification challenge (Deep Drilling Field). Our classifier scores an area under the curve (AUC) of 0.996 for binary classification (SN Ia or non-SN Ia) and 95.3% accuracy for three-class classification (SN Ia, SN Ibc, or SN II). Application of our binary classification to HSC transient data yields an AUC score of 0.925. With two weeks of HSC data since the first detection, this classifier achieves 78.1% accuracy for binary classification, and the accuracy increases to 84.2% with the full dataset. This paper discusses the potential use of machine learning for SN type classification purposes.

Takahashi, Ichiro↗
DOE OSTI2023

Partial-wave decomposition of the Keldysh ionization amplitude

We present an alternative way of calculating the Keldysh amplitude, i.e., the length-gauge form of the ionization amplitude in the strong-field approximation. The amplitude is evaluated exactly by expanding it in Fourier components and partial waves. Comparisons of the semianalytic model predictions with results of ab initio numerical simulations of the time-dependent Schrödinger equation for the interaction of electrons in short-range potentials with intense laser light yield excellent agreement, for wavelengths from the single photon to the multiphoton to the tunneling regime. Specifically, for ionization from initial states with higher angular momentum quantum number, e.g., p states, a significant improvement over predictions based on the popular saddle-point approximation is found. Furthermore, the current model rate allows for interpretation of the strong-field ionization process in terms of multiphoton absorption pathways and angular momentum selection rules.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Coriolis coupling effects in proton-pickup spectroscopic factors from 12 B

Spectroscopic factors to low-lying negative-parity states in Be 11 extracted from the B 12 ( d , He 3 ) Be 11 proton-removal reaction are interpreted within the rotational model. Earlier predictions of the p -wave proton-removal strengths in the strong-coupling limit of the Nilsson model underestimated the spectroscopic factors to the 3 / 2 1 - and 5 / 2 1 - states and suggested that deviations in the 1 + ground state of the odd-odd B 12 due to Coriolis coupling should be further explored. Furthermore, in this work we use the particle rotor model to take into account these effects and obtain a good description of the level scheme in B 11 , with a moderate K mixing of the proton Nilsson levels [110]1/2 and [101]3/2. This mixing, present in the 1 + bandhead of B 12 , is key to explaining the proton-pickup data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

New collective structures in Au 179 and their implications for the triaxial deformation of the Pt 178 core

The extremely neutron-deficient isotope 179 Au has been studied by a combination of in-beam γ-ray and isomeric-decay spectroscopy. For in-beam spectroscopy, the recoil-isomer tagging technique was employed, using the known 3/2 – , T 1/2 = 328 ns isomer. A new rotational band, associated with the unfavored signature band of the 1⁢ℎ 9/2 ⊕2f⁢ 7/2 proton-intruder configuration, was revealed. A previously unknown, high-spin isomeric state with an excitation energy of 1743(17) keV and T 1/2 = 2.16⁢(8) ⁢µs was discovered. Five decay paths were identified, some of them feeding previously unknown non-yrast excited states, associated with the 1⁢i 13/2 proton-intruder configuration. Calculations based on the particle-plus-triaxial-rotor model were performed to interpret the data. On the basis of these calculations, the new 1⁢ℎ 9/2 ⊕2f 7/2 rotational band is interpreted as due to triaxial deformation of the underlying configuration with β 2 ≈ 0.26 and γ ≈ 27°. In conclusion, observed non-yrast states of the positive-parity 1i 13/2 intruder configuration are interpreted as due to triaxial deformation with β 2 ≈ 0.26 and γ ≈ 20°.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Reinvestigation of the level structures of the even-even nuclei 90 Zr and 92 Zr

Excited states of 90 Zr and 92 Zr were investigated using the fusion reactions 6 Li + 89 Y and 14 N + 82 Se , respectively. Based on the experimental data, 5 and 18 new 𝛾 rays have been added to the level schemes of 90 Zr and 92 Zr , respectively. The level structures of 90 Zr and 92 Zr have been interpreted with shell-model calculations using the GWBXG and SNET effective interactions. The neutron core-breaking and the importance of the 1⁢𝑔 7/2 and 1⁢ℎ 11/2 orbits for high-spin states of 92 Zr were discussed. Finally, the excitation energy of the neutron core-breaking of nuclei in the 𝐴=90 region was compared.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Role of Local Structure in the Enhanced Dynamics of Deformed Glasses

External stress can accelerate molecular mobility of amorphous solids by several orders of magnitude. The changes in mobility are commonly interpreted through the Eyring model, which invokes an empirical activation volume. Here, we analyze constant-stress molecular dynamics simulations and propose a structure-dependent Eyring model, connecting activation volume to a machine-learned field, softness. We show that stress has a heterogeneous effect on the mobility that depends on local structure through softness. The barrier impeding relaxation reduces more for well-packed particles, which explains the narrower distribution of relaxation time observed under stress.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Probing Electronic Coherence between Core-Level Vacancies at Different Atomic Sites

The detailed understanding of electronic coherence in quantum systems requires measurements on the attosecond timescale. Attosecond x-ray pulses enable the study of electronic coherence in core-excited molecular systems. Here we report on the coherent motion of electrons in the 1,1-difluoroethylene ion following ionization of the K shell of the two nonequivalent carbon sites with a subfemtosecond x-ray pulse. Using the angular streaking technique to track the Auger-Meitner decay, we observe temporal modulations of the emission, indicating the electronic coherence of the core-excited ionic states, and extract a 6.5 ± 0.8 fs average lifetime of the core-level vacancies. A quantum-mechanical model is employed to interpret the measurement, and we find the observed temporal modulations are independent of charge density oscillations. This work opens a new regime of coherent electronic motion, beyond charge migration, where electronic coherence manifests in the nonlocal quantum correlation between atomic sites while charge density oscillation is absent. Our results broaden the landscape of electronic coherence in molecular systems. Published by the American Physical Society 2025

Wang, Jun (ORCID:000000031962895X)↗
DOE OSTI2022

A round-robin approach provides a detailed assessment of biomolecular small-angle scattering data reproducibility and yields consensus curves for benchmarking

Through an expansive international effort that involved data collection on 12 small-angle X-ray scattering (SAXS) and four small-angle neutron scattering (SANS) instruments, 171 SAXS and 76 SANS measurements for five proteins (ribonuclease A, lysozyme, xylanase, urate oxidase and xylose isomerase) were acquired. From these data, the solvent-subtracted protein scattering profiles were shown to be reproducible, with the caveat that an additive constant adjustment was required to account for small errors in solvent subtraction. Further, the major features of the obtained consensus SAXS data over the q measurement range 0–1 Å −1 are consistent with theoretical prediction. The inherently lower statistical precision for SANS limited the reliably measured q -range to <0.5 Å −1 , but within the limits of experimental uncertainties the major features of the consensus SANS data were also consistent with prediction for all five proteins measured in H 2 O and in D 2 O. Thus, a foundation set of consensus SAS profiles has been obtained for benchmarking scattering-profile prediction from atomic coordinates. Additionally, two sets of SAXS data measured at different facilities to q > 2.2 Å −1 showed good mutual agreement, affirming that this region has interpretable features for structural modelling. SAS measurements with inline size-exclusion chromatography (SEC) proved to be generally superior for eliminating sample heterogeneity, but with unavoidable sample dilution during column elution, while batch SAS data collected at higher concentrations and for longer times provided superior statistical precision. Careful merging of data measured using inline SEC and batch modes, or low- and high-concentration data from batch measurements, was successful in eliminating small amounts of aggregate or interparticle interference from the scattering while providing improved statistical precision overall for the benchmarking data set.

59 BASIC BIOLOGICAL SCIENCES↗