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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DOE OSTI2025

DONKEY: A Flexible and Accurate Algorithm for Clustering

We propose an accurate clustering algorithm suitable for the varied and multidimensional data sets that correspond to temporal snapshots from on-the-fly nonadiabatic trajectory-based simulations of photoexcited dynamics. The algorithm approximates the underlying probability density function using variable kernel density estimation, with local maxima corresponding to cluster centers. Each data point is then assigned to one of the maxima by employing a maximization procedure. Finally, clusters artificially separated by minor fluctuations in the probability density are merged. The algorithm does not require parameter tuning, which ensures flexibility and reduces the risk of bias. It is tested on several synthetic data sets, where it consistently outperforms conventional clustering algorithms. As a final example, the algorithm is applied to the excited dynamics of the norbornadiene ⇌ quadricyclane (C 7 H 8 ) molecular photoswitch, demonstrating how distinct reaction pathways can be identified.

algorithms↗
DOE OSTI2020

A Multiple Filter Based Neural Network Approach to the Extrapolation of Adsorption Energies on Metal Surfaces for Catalysis Applications

Computational catalyst discovery involves the development of microkinetic reactor models based on estimated parameters determined from density functional theory (DFT). For complex surface chemistries, the number of reaction intermediates can be very large, and the cost of calculating the adsorption energies by DFT for all surface intermediates even for one active site model can become prohibitive. In this paper, we have identified appropriate descriptors and machine learning models that can be used to predict a significant part of these adsorption energies given data on the rest of them. Furthermore, our investigations also included the case when the species data used to train the predictive model are of different size relative to the species the model tries to predict—this is an extrapolation in the data space which is typically difficult with regular machine learning models. Due to the relative size of the available data sets, we have attempted to extrapolate from the larger species to the smaller ones in the current work. Here, we have developed a neural network based predictive model that combines an established additive atomic contribution based model with the concepts of a convolutional neural network that, when extrapolating, achieves a statistically significant improvement over the previous models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Towards Prediction of Non-Radiative Decay Pathways in Organic Compounds I: The Case of Naphthalene Quantum Yields

Many emerging technologies depend on human’s ability to control and manipulate the excited-state properties of molecular systems. These technologies include fluorescent labeling in biomedical imaging, light harvesting in photovoltaics, and electroluminescence in light-emitting devices. All of these systems suffer from non-radiative loss pathways that dissipate electronic energy as heat, which causes the overall system efficiency to be directly linked to quantum yield (Φ) of the molecular excited state. Unfortunately, Φ is very difficult to predict from first principles because the description of a slow non-radiative decay mechanism requires an accurate description of long-timescale excited-state quantum dynamics. In the present study, we introduce an efficient semi-empirical method of calculating the fluorescence quantum yield (Φ fl ) for molecular chromophores, which converts simple electronic energies computed using time-dependent density functional theory (TDDFT) into an estimate of Φ fl . As with all machine learning strategies, the algorithm needs to be trained on fluorescent dyes for which Φ fl ’s are known, so as to provide a black-box method which can later predict Φfl’s for chemically similar chromophores that have not been studied experimentally. Here, as a first illustration of how our proposed algorithm can be trained, we examine a family of 25 naphthalene derivatives. The simplest application of the energy gap law is found to be inadequate to explain the rates of internal conversion (IC) or intersystem crossing (ISC) – the electronic properties of at least one higher-lying electronic state (S n or T n ) or one far-from-equilibrium geometry are typically needed to obtain accurate results. Indeed, the key descriptors turn out to be the transition state between the Franck–Condon minimum and a distorted local minimum near an S 0 /S 1 conical intersection (which governs IC) and the magnitude of the spin-orbit coupling (which governs ISC). The resulting Φ fl ’s are predicted with reasonable accuracy (~ 22%), making our approach a promising ingredient for high-throughput screening and rational design of the molecular excited states with desired Φ fl ’s. We thus conclude that our model, while semi-empirical in nature, does in fact extract sound physical insight into the challenge of describing non-radiative relaxations.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Coherent Spins in van der Waals Semiconductor GeS 2 at Ambient Conditions

Optically active spin defects in van der Waals (vdW) materials have emerged as versatile quantum sensors, enabling applications for a wide range of quantum phenomena in condensed matter systems. Their ease of exfoliation and compatibility with device integration make them promising candidates for future quantum technologies. Here we report the observation and room-temperature coherent control of ensemble spin defects in the high-temperature crystalline phase of germanium disulfide (β-GeS 2 ), a two-dimensional (2D) semiconductor with low nuclear spin density. The defects exhibit spin-1/2 behavior, and their dynamics can be explained by a weakly coupled spin-pair model. We implement dynamical decoupling techniques to extend the coherence time (T 2 ) by a factor of 20. Finally, we use density functional theory (DFT) calculations to estimate the structures and spin densities of two possible spin defect candidates. This work will help to expand the field of quantum sensing with spin defects in 2D materials.

2D materials↗
DOE OSTI2020

Emergence of unprecedented climate change in projected future precipitation

The future time of emergence when precipitation changes due to anthropogenic influences begins to continuously exceed the previous maximum value is defined as the ‘tipping year’ Historical experiments and future experiments simulated by state-of-the-art climate models were utilized. A total of 510,000 time series from year 1856 to 2095 were generated by sampling the natural internal variability in precipitation. The time evolutions of internal variability in the whole time period were estimated from the combination of past and future experiments with preindustrial control experiments. A large ensemble size enabled an estimation of the probability density function of the tipping year at each grid point, providing precise information on the uncertainty of the projection. The tipping year of average precipitation emerges earlier in high latitudes than in lower latitudes. In some regions in lower latitudes and mid-latitudes, the tipping year of intense precipitation emerges faster than that of average precipitation. The tipping years of average and intense precipitation are earlier for higher anthropogenic forcing scenarios than for lower scenarios. The global average of the tipping year for intense precipitation might be attributed to the enhancement of the thermodynamic effect (moisture) rather than the dynamic effect (vertical motion).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Revisiting the pseudo-supercritical path method: An improved formulation for the alchemical calculation of solid–liquid coexistence

Alchemical free energy calculations via molecular dynamics have been applied to obtain thermodynamic properties related to solid–liquid equilibrium conditions, such as melting points. In recent years, the pseudo-supercritical path (PSCP) method has proved to be an important approach to melting point prediction due to its flexibility and applicability. In the present work, we propose improvements to the PSCP alchemical cycle to make it more compact and efficient through a concerted evaluation of different potential energies. The multistate Bennett acceptance ratio (MBAR) estimator was applied at all stages of the new cycle to provide greater accuracy and uniformity, which is essential concerning uncertainty calculations. In particular, for the multistate expansion stage from solid to liquid, we employed the MBAR estimator with a reduced energy function that allows affine transformations of coordinates. Free energy and mean derivative profiles were calculated at different cycle stages for argon, triazole, propenal, and the ionic liquid 1-ethyl-3-methyl-imidazolium hexafluorophosphate. Comparisons showed a better performance of the proposed method than the original PSCP cycle for systems with higher complexity, especially the ionic liquid. Furthermore, a detailed study of the expansion stage revealed that remapping the centers of mass of the molecules or ions is preferable to remapping the coordinates of each atom, yielding better overlap between adjacent states and improving the accuracy of the methodology.

25 ENERGY STORAGE↗
DOE OSTI2024

Optically multiplexed neutron time-of-flight technique for inertial confinement fusion

Neutron time-of-flight (nTOF) detectors are crucial in diagnosing the performance of inertial confinement fusion (ICF) experiments, which implode targets of deuterium–tritium fuel to achieve thermonuclear conditions. These detectors utilize the fusion neutron energy spectrum to extract key measurements, including the hotspot ion temperature and fuel areal density. Previous work [Danly et al., Rev. Sci. Instrum. 94, 043502 (2023)] has demonstrated adding 1D spatial resolution to an nTOF-like detector using a neutron aperture and streak camera to measure the ion temperature profile of an ICF implosion. By contrast, the study presented herein explores modifying the 1D detector to use a fast photomultiplier tube (PMT) to validate the design of a 2D spatially resolved instrument based on reconstruction from 1D profiles. The modification would collect time-of-flight traces from separate scintillators in an imaging array with one PMT using optical fibers of varying lengths to time-multiplex the signals. This technique has been demonstrated in ride-along experiments on the OMEGA laser with 20 fiber-coupled scintillator channels connected to a Photek PMT210. Results provide constraints on the fiber lengths and PMT gating requirements to promote pulse fidelity throughout all channels. Calibration of the detector to fixed nTOFs can provide a preliminary estimate of the instrument response function (IRF), although measurement of the IRF is currently under way. These results suggest that nTOF signals can potentially be time-multiplexed with fibers so long as the design is strategic to mitigate signal-to-noise reduction, modal dispersion, and charge build-up in the PMT, which has implications beyond ion temperature imaging.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

On the synchrotron emission in kinetic simulations of runaway electrons in magnetic confinement fusion plasmas

Developing avoidance or mitigation strategies of runaway electrons (REs) in magnetic confinement fusion (MCF) plasmas is of crucial importance for the safe operation of ITER. In order to develop these strategies, an accurate diagnostic capability that allows good estimates of the RE distribution function in these plasmas is needed. Synchrotron radiation (SR) of RE in MCF, besides of being one of the main damping mechanisms for RE in the high energy relativistic regime, is routinely used in current MCF experiments to infer the parameters of RE energy and pitch angle distribution functions. In the present paper we address the long standing question about what are the relationships between different REs distribution functions and their corresponding synchrotron emission simultaneously including: full-orbit effects, information of the spectral and angular distribution of SR of each electron, and basic geometric optics of a camera. We study the spatial distribution of the SR on the poloidal plane, and the statistical properties of the expected value of the synchrotron spectra of REs. Here we observe a strong dependence of the synchrotron emission measured by the camera on the pitch angle distribution of runaways, namely we find that crescent shapes of the spatial distribution of the SR as measured by the camera relate to RE distributions with small pitch angles, while ellipse shapes relate to distributions of runaways with larger the pitch angles. A weak dependence of the synchrotron emission measured by the camera with the RE energy, value of the q-profile at the edge, and the chosen range of wavelengths is observed. Furthermore, we find that oversimplifying the angular dependence of the SR changes the shape of the synchrotron spectra, and overestimates its amplitude by approximately 20 times for avalanching runaways and by approximately 60 times for mono-energetic distributions of runaways.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

pKPDB: a protein data bank extension database of p Ka and pI theoretical values

Abstract Summary pKa values of ionizable residues and isoelectric points of proteins provide valuable local and global insights about their structure and function. These properties can be estimated with reasonably good accuracy using Poisson–Boltzmann and Monte Carlo calculations at a considerable computational cost (from some minutes to several hours). pKPDB is a database of over 12 M theoretical pKa values calculated over 120k protein structures deposited in the Protein Data Bank. By providing precomputed pKa and pI values, users can retrieve results instantaneously for their protein(s) of interest while also saving countless hours and resources that would be spent on repeated calculations. Furthermore, there is an ever-growing imbalance between experimental pKa and pI values and the number of resolved structures. This database will complement the experimental and computational data already available and can also provide crucial information regarding buried residues that are under-represented in experimental measurements. Availability and implementation Gzipped csv files containing p Ka and isoelectric point values can be downloaded from https://pypka.org/pKPDB. To query a single PDB code please use the PypKa free server at https://pypka.org. The pKPDB source code can be found at https://github.com/mms-fcul/pKPDB. Supplementary information Supplementary data are available at Bioinformatics online.

Reis, Pedro B. P. S. (ORCID:0000000335636239)↗
DOE OSTI2022

Regression of exchangeable relational arrays

Relational arrays represent measures of association between pairs of actors, often in varied contexts or over time. Trade flows between countries, financial transactions between individuals, contact frequencies between school children in classrooms and dynamic protein-protein interactions are all examples of relational arrays. Elements of a relational array are often modelled as a linear function of observable covariates. Uncertainty estimates for regression coefficient estimators, and ideally the coefficient estimators themselves, must account for dependence between elements of the array, e.g., relations involving the same actor. Existing estimators of standard errors that recognize such relational dependence rely on estimating extremely complex, heterogeneous structure across actors. This paper develops a new class of parsimonious coefficient and standard error estimators for regressions of relational arrays. Here we leverage an exchangeability assumption to derive standard error estimators that pool information across actors, and are substantially more accurate than existing estimators in a variety of settings. This exchangeability assumption is pervasive in network and array models in the statistics literature, but not previously considered when adjusting for dependence in a regression setting with relational data. We demonstrate improvements in inference theoretically, via a simulation study, and by analysis of a dataset involving international trade.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Chromatic effects on the PSF and shear measurement for the Roman Space Telescope High-Latitude Wide Area Survey

Weak gravitational lensing (WL) is a key cosmological probe that requires precise measurement of galaxy images to infer shape distortions, or shear, and constrain cosmology. Accurate estimation of the point spread function (PSF) is crucial for shear measurement, but the wavelength dependence of the PSF introduces chromatic biases that can systematically impact shear inference. We focus on biases arising from spectral energy distribution (SED) differences between stars, used for PSF modelling, and galaxies, used for shear measurement. We investigate these effects in Roman’s four design reference mission WL bands (Y106, J129, H158, F184) and wide filter (W146). Using Roman-like image simulations, we quantify the induced shear biases and compare them to requirements on those biases. Multiplicative biases over all galaxies hover around ~0.2 per cent in the WL bands and 2 per cent in the wide filter, exceeding the mission requirement of |m| < 0.032 per cent and relaxed requirement of |m| < 0.1 per cent⁠. In individual redshift bins, biases can reach 0.4–0.9 per cent for the WL bands and 3–6 per cent for the wide filter. Additive biases remain acceptable in the WL bands but exceed systematic limits in the wide filter. We develop and test PSF-level corrections, showing that a first-order correction reduces biases within survey requirements for the WL bands; however, higher-order terms are necessary for the wide filter. Our results highlight the necessity of chromatic corrections for precision WL with Roman and provide a framework for mitigating these biases. Finally, we compare analytical colour-based corrections to self-organizing maps and find that both methods effectively reduce biases.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Remote detection of radioactive material using a short-pulse CO 2 laser

Detection of radioactive material at distances greater than the radiated particle range is an important goal with applications in areas such as national defense and disaster response. Here, we demonstrate avalanche-breakdown-based remote detection of a 3.6 mCi α-particle source at a standoff distance of 10 m, using 70 ps, long-wave infrared (λ = 9.2 µm) CO 2 laser pulses. This is ∼10 times longer than our previous results using a mid-IR laser. The primary detection method is direct backscatter from microplasmas generated in the laser focal volume. The backscatter signal is amplified as it propagates back through the CO 2 laser chain, enhancing sensitivity by >100 times. Here we also characterize breakdown plasmas with fluorescence imaging, and present a simple model to estimate backscattered signals as a function of the seed density profile in the laser focal volume. All of this is achieved with a relatively long-drive laser focal geometry (f/200) that is readily scalable to >100 m.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Solar neutrino detection in liquid xenon detectors via charged-current scattering to excited states

We investigate the prospects for real-time detection of solar neutrinos via the charged-current neutrino-nucleus scattering process in liquid xenon time projection chambers. We use a nuclear shell model, benchmarked with experimental data, to calculate the cross sections for populating specific excited states of the cesium nuclei produced by neutrino capture on Xe 131 and Xe 136 . The shell model is further used to compute the decay schemes of the low-lying 1 + excited states of Cs 136 , for which there is sparse experimental data. We explore the possibility of tagging the characteristic deexcitation γ rays/conversion electrons using two techniques: spatial separation of their energy deposits using event topology and their time separation using delayed coincidence. The efficiencies in each case are evaluated within a range of realistic detector parameters. We find that the topological signatures are likely to be dominated by radon backgrounds, but that a delayed-coincidence signature from long-lived states predicted in Cs 136 may enable background-free detection of CNO neutrino interactions in next-generation experiments with smaller uncertainty than current measurements. We also estimate the sensitivity as a function of exposure for detecting the solar-temperature-induced line shift in Be 7 neutrino emission, which may provide a new test of solar models.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Primary intrinsic defects and their charge transition levels in β–Ga 2 O 3

A steady-state photocapacitance (SSPC) setup directly connected to the beamline of a MeV ion implanter is utilized to study primary intrinsic defects in β – Ga 2 O 3 generated by He implantation at cryogenic temperatures (120 K). At low temperatures, the migration of defects is suppressed, and hence the generation of primary intrinsic defects is expected to prevail. SSPC measurements reveal defect-related optical transitions in halide vapor-phase epitaxy (HVPE) -grown β – Ga 2 O 3 thin films with onset energies at 1.3 ( T 1 ) , 1.7 ( T 2 ) , 1.9 ( T 3 ) , 2.6 ( T 4 ) , 3.7 ( T 5 ) , and 4.2 eV ( T 6 ) . T 2 , T 4 , T 5 , and T 6 were observed in as-received HVPE-grown β – Ga 2 O 3 thin films, whereby T 2 is only sporadically observed. The introduction rates for T 3 , T 4 , as well as T 6 indicate an origin related to primary intrinsic defects. Notably, T 1 and T 3 are only observed after He implantation at cryogenic temperatures. Hybrid-functional calculations were performed to estimate the optical absorption cross-section spectra for the gallium ( Ga i ) and oxygen ( O i ) interstitials as well as the corresponding vacancies ( V Ga and V O , respectively), and compared with the measured onsets for optical absorption found by SSPC measurements. Indeed, we propose T 3 to be associated with Ga i ( + / + 2 ) and/or V GaI ( - 3 / - 2 ) , while T 4 is suggested to be related to V O K ( 0 / + ) ( K = I , II , III ) and/or V GaII ( - 3 / - 2 ) . Additionally, several further charge-state transition levels associated with V GaI and V GaII may contribute to T 4 and T 6 . We further studied the kinetics of the defects created with He implantation by exposing the sample to room temperature. The kinetics observed for T 3 and T 4 further support the proposed assignments of the corresponding defect signatures.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Model-based Cyber-attack Detection for Voltage Source Converters in Island Microgrids

With the upgrading of communication and control in microgrids, cyber threats on the power converters are increasing. Here, in this paper, a novel model-based cyber-attack detection methodology is proposed for each voltage source converter in microgrids. The Harmonics State Space Matrix (H-Matrix) is used to build the closed-loop transfer function, providing model-based estimation with the grid voltage and control reference. Then, the space phase model (SPM) is used to calculate residual to detect cyber-attacks in voltage source converter (VSC). As controller and converter parameters are included in the H-matrix, the proposed method also could detect cyber-attacks when voltage fluctuation occurs in the grid. To verify the feasibility of the proposed method, several attacks targeting VSC in an islanded microgrid are simulated in MATLAB. Simulation and detection results are introduced to demonstrate the resilience and feasibility of the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Distributional Deep Reinforcement Learning-Based Emergency Frequency Control

Emergency frequency control is one of the most critical approaches to maintain power system stability after major disturbances. With the increasing number of grid-connected renewable energy sources, existing model-based methods of frequency control are facing up with challenges of computational speed and scalability for large-scale systems. In this paper, the emergency frequency control problem is formulated as a Markov Decision Process (MDP) and solved through a novel Distributional Deep Reinforcement Learning (DDRL) method, namely the distributional soft actor critic (DSAC) method. Compared with other RL methods that only estimate the mean value, the proposed DSAC model estimates the distribution of value function over returns. This advancement can lead to more insights and knowledge for the agent, with the benefit of a much faster and more stable learning process, and the improved frequency control performance. Here, the simulation results on IEEE 39-bus and IEEE 118-bus systems demonstrate the effectiveness and robustness of proposed models, as well as the advantage compared to other state-of-the-art DRL algorithms.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Effect of Light Water Reactor Water Environments on the Fatigue Life of Reactor Materials

The American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code (Code) provides rules for the design of Class 1 components of nuclear power plants. Figures I-9.1 through I-9.6 of Appendix I to Section III of the Code specify fatigue design curves for applicable structural materials. However, the Code design curves do not explicitly address the effects of light water reactor (LWR) water environments. Existing fatigue strain-vs.-life (ε-N) laboratory data illustrate potentially significant effects of LWR water environments on the fatigue resistance of pressure vessel and piping steels. Extensive studies have been conducted at Argonne National Laboratory and elsewhere since 1990 to investigate the effects of LWR environments on the fatigue life of piping and pressure vessel steels. This article summarizes the results of these studies. Existing fatigue ε-N data were evaluated to identify the various material, environmental, and loading conditions that influence fatigue crack initiation; a methodology for estimating fatigue lives as a function of these parameters was developed. The effects were incorporated into the ASME Code Section III fatigue evaluations in terms of an environmental correction factor, F en , which is defined as the ratio of fatigue life in air at room temperature to the fatigue life in the LWR water environment at reactor operating temperatures. Available fatigue data were used to develop fatigue design curves for carbon and low-alloy steels, austenitic stainless steels, and nickel-chromium-iron (NiCr-Fe) alloys and their weld metals in air at room temperature. A review of the Code Section III fatigue adjustment factors of 2 on strain and 20 on life is also presented and the possible conservatism inherent in the choice of these adjustment factors is evaluated. A brief description of potential effects of neutron irradiation on fatigue crack initiation for these structural materials is also presented.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Quantification and prediction of error in MIMO tests

Dynamic testing of systems is most realistic of real-world conditions when multiple input and multiple output (MIMO) techniques are used. To replicate measured environmental conditions, a series of desired outputs (responses) on the system must be realized by inverting the frequency response functions (FRF) matrix for input estimation. System identification is dependent on the number of inputs and outputs, which affect the type of solutions. In input estimation, the auto spectra of the determined inputs are affected by both the auto spectra and cross spectra of the desired outputs. This research evaluates errors and investigates two sources in an experimental setting. The first significant error source is test-to-test variability in FRFs from system identification tests, quantified by magnitude variability from long-duration tests. The second significant error source is the realization of time histories from frequency domain inputs. The spectral content of the realized random process deviates from the desired content and is also quantified. The structure is a linear three-story frame fixed at the base; two inputs are provided uniaxially with the use of suspended electrodynamic shakers. The proposed model for error sources was found to be effective in predicting errors in a SISO (single-input single-output) and a square (2-input 2-output) MIMO test.

Yousef, Odey↗