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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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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A Novel Active Optimization Approach for Rapid and Efficient Design Space Exploration Using Ensemble Machine Learning

In this work, a novel design optimization technique based on active learning, which involves dynamic exploration and exploitation of the design space of interest using an ensemble of machine learning algorithms, is presented. In this approach, a hybrid methodology incorporating an explorative weak learner (regularized basis function model) that fits high-level information about the response surface and an exploitative strong learner (based on committee machine) that fits finer details around promising regions identified by the weak learner is employed. For each design iteration, an aristocratic approach is used to select a set of nominees, where points that meet a threshold merit value as predicted by the weak learner are selected for evaluation. In addition to these points, the global optimum as predicted by the strong learner is also evaluated to enable rapid convergence to the actual global optimum once the most promising region has been identified by the optimizer. Additionally, this methodology is first tested by applying it to the optimization of a two-dimensional multi-modal surface and, subsequently, to a complex internal combustion (IC) engine combustion optimization case with nine control parameters related to fuel injection, initial thermodynamic conditions, and in-cylinder flow. It is found that the new approach significantly lowers the number of function evaluations that are needed to reach the optimum design configuration (by up to 80%) when compared to conventional optimization techniques, such as particle swarm and genetic algorithm-based optimization techniques.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

A novel active optimization approach for rapid and efficient design space exploration using ensemble machine learning

In this work, a novel design optimization technique based on active learning, which involves dynamic exploration and exploitation of the design space of interest using an ensemble of machine learning algorithms, is presented. In this approach, a hybrid methodology incorporating an explorative weak learner (regularized basis function model) which fits high-level information about the response surface, and an exploitative strong learner (based on committee machine) that fits finer details around promising regions identified by the weak learner, is employed. For each design iteration, an aristocratic approach is used to select a set of nominees, where points that meet a threshold merit value as predicted by the weak learner are selected to be evaluated using expensive function evaluation. In addition to these points, the global optimum as predicted by the strong learner is also evaluated to enable rapid convergence to the actual global optimum once the most promising region has been identified by the optimizer. This methodology is first tested by applying it to the optimization of a two-dimensional multi-modal surface. The performance of the new active learning approach is compared with traditional global optimization methods, namely micro-genetic algorithm (pGA) and particle swarm optimization (PSO). It is demonstrated that the new optimizer is able to reach the global optimum much faster with a significantly fewer number of function evaluations. Subsequently, the new optimizer is also applied to a complex internal combustion (IC) engine combustion optimization case with nine control parameters related to fuel injection, initial thermodynamic conditions, and in-cylinder flow. It is again found that the new approach significantly lowers the number of function evaluations that are needed to reach the optimum design configuration (by up to 80%) when compared to particle swarm and genetic algorithm-based optimization techniques.

Machine learning, active learning, design optimiza↗
DOE OSTI2021

Near-Field Radiative Heat Transfer Eigenmodes

The near-field electromagnetic interaction between nanoscale objects produces enhanced radiative heat transfer that can greatly surpass the limits established by far-field blackbody radiation. Here, we present a theoretical framework to describe the temporal dynamics of the radiative heat transfer in ensembles of nanostructures, which is based on the use of an eigenmode expansion of the equations that govern this process. Using this formalism, we identify the fundamental principles that determine the thermalization of collections of nanostructures, revealing general but often unintuitive dynamics. Overall, our results provide an elegant and precise approach to efficiently analyze the temporal dynamics of the near-field radiative heat transfer in systems containing a large number of nanoparticles.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Dynamic Behavior of Bound Interlayer Excitons in Interlayer-Doped Cs 3 Bi 2 Br 9 Vacancy-Ordered Perovskite

Interlayer doping of the vacancy-ordered 2D perovskite Cs 3 Bi 2 Br 9 (CBB) enables the formation of bound interlayer excitons (BIEs), a unique charge-transfer excited state within the layered solid. BIEs previously reported with silver (Ag + ) as an interlayer dopant exhibited bright broadband photoluminescence (PL) with prolonged lifetime at room temperature, offering potential applications in efficient white light emission, photocatalysis, and optoelectronics. However, the dynamic behavior of radiation and excited carriers remains poorly understood due to the limitations of ensemble spectroscopic measurements. Here, we investigate the temperature-dependent dynamics of Ag-doped Cs 3 Bi 2 Br 9 (Ag-CBB) using single-particle time-resolved PL spectroscopy and ultrafast transient absorption imaging. Single-particle PL measurements reveal three distinct emission regimes across temperature: (i) BIE-dominant emission at high temperatures, (ii) a mixture of radiation from BIEs and self-trapped excitons (STEs) at intermediate temperatures, and (iii) STE-dominant emission below 100 K. Rapid transient absorption mapping using Parallel Rapid Imaging with Spectroscopic Mapping (PRISM) reveals subpicosecond STE formation in pristine CBB and long-lived photoinduced absorption by BIEs, consistent with electron–hole separation and suppressed STE transfer. The spatial uniformity of these signals confirms homogeneous Ag doping across single crystals. These findings highlight the role of Ag interlayer dopants in governing the BIE dynamics.

bound interlayer exciton↗
DOE OSTI2023

Adaptive Pore Opening to Form Tailored Adsorption Sites in a Cooperatively Flexible Framework Enables Record Inverse Propane/Propylene Separation

A proposed low-energy alternative to the separation of alkanes from alkenes by energy-intensive cryogenic distillation is separation by porous adsorbents. Unfortunately, most adsorbents preferentially take up the desired, high-value major component alkene, requiring frequent regeneration. Adsorbents with inverse selectivity for the minor component alkane would enable the direct production of purified, reagent-grade alkene, greatly reducing global energy consumption. However, such materials are exceedingly rare, especially for propane/propylene separation. Here, we report that through adaptive and spontaneous pore size and shape adaptation to optimize an ensemble of weak noncovalent interactions, the structurally responsive metal-organic framework CdIF-13 (sod-Cd(benzimidazolate) 2 ) exhibits inverse selectivity for propane over propylene with record-setting separation performance under industrially relevant temperature, pressure, and mixture conditions. Powder synchrotron X-ray diffraction measurements combined with first-principles calculations yield atomic-scale insight and reveal the induced fit mechanism of adsorbate-specific pore adaptation and ensemble interactions between ligands and adsorbates. Dynamic column breakthrough measurements confirm that CdIF-13 displays selectivity under mixed-component conditions of varying ratios, with a record measured selectivity factor of α ≈ 3 at 95:5 propylene:propane at 298 K and 1 bar. When sequenced with a low-cost rigid adsorbent, we demonstrated the direct purification of propylene under ambient conditions. In conclusion, this combined atomic-level structural characterization and performance testing firmly establishes how cooperatively flexible materials can be capable of unprecedented separation factors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Structural mechanisms for binding and activation of a contact-quenched fluorophore by RhoBAST

The fluorescent light-up aptamer RhoBAST, which binds and activates the fluorophore–quencher conjugate tetramethylrhodamine-dinitroaniline with high affinity, super high brightness, remarkable photostability, and fast exchange kinetics, exhibits excellent performance in super-resolution RNA imaging. Here we determine the co-crystal structure of RhoBAST in complex with tetramethylrhodamine-dinitroaniline to elucidate the molecular basis for ligand binding and fluorescence activation. The structure exhibits an asymmetric “A”-like architecture for RhoBAST with a semi-open binding pocket harboring the xanthene of tetramethylrhodamine at the tip, while the dinitroaniline quencher stacks over the phenyl of tetramethylrhodamine instead of being fully released. Molecular dynamics simulations show highly heterogeneous conformational ensembles with the contact-but-unstacked fluorophore–quencher conformation for both free and bound tetramethylrhodamine-dinitroaniline being predominant. The simulations also show that, upon RNA binding, the fraction of xanthene-dinitroaniline stacked conformation significantly decreases in free tetramethylrhodamine-dinitroaniline. This highlights the importance of releasing dinitroaniline from xanthene tetramethylrhodamine to unquench the RhoBAST–tetramethylrhodamine-dinitroaniline complex. Using SAXS and ITC, we characterized the magnesium dependency of the folding and binding mode of RhoBAST in solution and indicated its strong structural robustness. The structures and binding modes of relevant fluorescent light-up aptamers are compared, providing mechanistic insights for rational design and optimization of this important fluorescent light-up aptamer-ligand system.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Light-quark connected intermediate-window contributions to the muon 𝑔 − 2 hadronic vacuum polarization from lattice QCD

We present a lattice-QCD calculation of the light-quark connected contribution to window observables associated with the leading-order hadronic vacuum polarization contribution to the anomalous magnetic moment of the muon, $a^{HVP,LO}_μ$. We employ the MILC Collaboration’s isospin-symmetric QCD gauge-field ensembles, which contain four flavors of dynamical highly improved staggered quarks with four lattice spacings between $a ≈ 0.06-0.15$ fm and close-to-physical quark masses. We consider several effective-field-theory-based schemes for finite volume and other lattice corrections and combine the results via Bayesian model averaging to obtain robust estimates of the associated systematic uncertainties. After unblinding, our final results for the intermediate and "W2" windows are $a^{U,W}_μ$(conn) = 206.6(1.0) x 10 -10 and $a^{U,W2}_μ$ (conn) = 100.7(3.2) x 10 -10 , respectively

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

The structural plasticity of nucleic acid duplexes revealed by WAXS and MD

Double-stranded DNA (dsDNA) and RNA (dsRNA) helices display an unusual structural diversity. Some structural variations are linked to sequence and may serve as signaling units for protein-binding partners. Therefore, elucidating the mechanisms and factors that modulate these variations is of fundamental importance. While the structural diversity of dsDNA has been extensively studied, similar studies have not been performed for dsRNA. Because of the increasing awareness of RNA’s diverse biological roles, such studies are timely and increasingly important. We integrate solution x-ray scattering at wide angles (WAXS) with all-atom molecular dynamics simulations to explore the conformational ensemble of duplex topologies for different sequences and salt conditions. These tightly coordinated studies identify robust correlations between features in the WAXS profiles and duplex geometry and enable atomic-level insights into the structural diversity of DNA and RNA duplexes. Notably, dsRNA displays a marked sensitivity to the valence and identity of its associated cations.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Bespoke Liquid/Liquid Interfaces (Final Technical Report)

The goal of DE-SC0001815 was to advance the basic science of liquid:liquid interface formation, to develop a deeper understanding of the mechanisms of phase separation and the essential relationships between solution composition, organization and dynamics that underlie the kinetic regime of solvent extraction. This included learning how interfacial organization and dynamics alters the properties of the primary coordination sphere of ions and the free energy of transport of ions complexes across a phase boundary. We relied primarily upon classical molecular dynamics studies to determine the equilibrium ensembles of these complex systems, but also utilized ab-initio MD and cluster-based density functional theory (DFT) calculations when more detailed investigation of the electronic structure was needed. We continued development of graph-theory based analyses to elucidate hierarchical correlations and expanded into geometric topology methods to quantify the collectively organized structures that can organize at a liquid/liquid interface during solute transport. One of the main conclusions was from the observation of two distinct mechanisms for solute transport - those that derive from amplifications of interfacial heterogeneity and surface roughness, and those wherein surface roughness has been dampened and instead collectively organized macrostructures work to bring solutes into the organic phase. It was our aim to create a concrete chemical model of the underlying driving forces behind interfacial primary and secondary structure formation and to map out the energetic features of solute transport so that tailored liquid/liquid can be developed that have characteristic kinetic features associated with mass transport.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Modeling the Electronic Absorption Spectra of the Indocarbocyanine Cy3

Accurate modeling of optical spectra requires careful treatment of the molecular structures and vibronic, environmental, and thermal contributions. The accuracy of the computational methods used to simulate absorption spectra is limited by their ability to account for all the factors that affect the spectral shapes and energetics. The ensemble-based approaches are widely used to model the absorption spectra of molecules in the condensed-phase, and their performance is system dependent. The Franck–Condon approach is suitable for simulating high resolution spectra of rigid systems, and its accuracy is limited mainly by the harmonic approximation. In this work, the absorption spectrum of the widely used cyanine Cy3 is simulated using the ensemble approach via classical and quantum sampling, as well as, the Franck–Condon approach. The factors limiting the ensemble approaches, including the sampling and force field effects, are tested, while the vertical and adiabatic harmonic approximations of the Franck–Condon approach are also systematically examined. Our results show that all the vertical methods, including the ensemble approach, are not suitable to model the absorption spectrum of Cy3, and recommend the adiabatic methods as suitable approaches for the modeling of spectra with strong vibronic contributions. We find that the thermal effects, the low frequency modes, and the simultaneous vibrational excitations have prominent contributions to the Cy3 spectrum. The inclusion of the solvent stabilizes the energetics significantly, while its negligible effect on the spectral shapes aligns well with the experimental observations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Online LIBS–ML Framework for Dynamic Characterization of Heterogeneous Waste-Derived Gasification Feedstocks

LIBS−ML framework for real time feedstock characterization during continuous conveyor transport Heterogeneous waste derived feedstocks (e.g., waste coal, biomass and blends) introduce rapid variability in heating value and ash chemistry that affect gasifier operation, yet conventional laboratory characterization techniques are too slow to support proactive control. To address this gap, this study reports on an online, in situ, dynamic characterization framework that couple’s laser-induced breakdown spectroscopy (LIBS) with leakage safe machine learning (ML) regression to deliver real time, decision quality predictions of gasifier relevant properties. A controlled sample matrix spanning two different waste coals, two different biomasses, and engineered blends under two particle size conditions were constructed and benchmarked using standardized laboratory analyses for proximate/ultimate properties and ash composition. LIBS spectra were acquired dynamically as material flowed on a conveyor belt, using high energy 1064 nm laser ablation and shot averaging to improve repeatability and precision. Supervised regression models (multi layer perceptron (MLP) /artificial neural network (ANN), random forest (RF), and support vector regression (SVR)) and an optimized weighted ensemble were trained on emission line feature sets using nested cross validation with Bayesian hyperparameter tuning and validated against an independent hold out set. The proposed LIBS−ML workflow achieves near laboratory predictive fidelity across parametric targets (including higher heating value (HHV), ash content, fixed carbon, sulfur, major ash forming oxides, and initial deformation temperature (IDT)), with the weighted ensemble providing a robust default predictor under dynamic measurement conditions. These results demonstrate a practical pathway for real time feedstock characterization that can enable feedforward adjustments and more resilient gasifier operation for variable quality waste derived fuels.

Biomass↗
DOE OSTI2020

The Great Inequality and the Dynamical Disintegration of the Outer Solar System

Using an ensemble of N-body simulations, this paper considers the fate of the outer gas giants (Jupiter, Saturn, Uranus, and Neptune) after the Sun leaves the main sequence and completes its stellar evolution. Due to solar mass loss—which is expected to remove roughly half of the star’s mass—the orbits of the giant planets expand. This adiabatic process maintains the orbital period ratios, but the mutual interactions between planets and the width of mean-motion resonances (MMR) increase, leading to the capture of Jupiter and Saturn into a stable 5:2 resonant configuration. The expanded orbits, coupled with the large-amplitude librations of the critical MMR angle, make the system more susceptible to perturbations from stellar flyby interactions. Accordingly, within about 30 Gyr, stellar encounters perturb the planets onto the chaotic subdomain of the 5:2 resonance, triggering a large-scale instability, which culminates in the ejections of all but one planet over the subsequent ∼10 Gyr. After an additional ∼50 Gyr, a close stellar encounter (with a perihelion distance less than ∼200 au) liberates the final planet. Through this sequence of events, the characteristic timescale over which the solar system will be completely dissolved is roughly 100 Gyr. Our analysis thus indicates that the expected dynamical lifetime of the solar system is much longer than the current age of the universe, but is significantly shorter than previous estimates.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Enhancing Extreme Precipitation Predictions With Dynamical Downscaling: A Convection‐Permitting Modeling Study in Texas and Oklahoma

Precipitation in the Southern Plains of the United States is relatively well depicted by the Community Earth System Model (CESM). However, despite its ability to capture seasonal mean precipitation anomalies, CESM consistently underestimates extreme pluvial and drought events, rendering it an insufficient tool for extending simulation lead times for exceptional events, such as the abnormally dry May 2011, which helped drive Texas into its worst period of drought in more than a century, and the abnormally wet May 2015, which led to widespread flooding in that state. Ensemble‐based regional climate experiments are completed for the two extreme years using Weather Research and Forecasting model (WRF) and downscaled from CESM. WRF simulations are at convection‐permitting grid resolution for improved physical representation of simulated precipitation over the Southern Great Plains. By integrating convection‐permitting models (CPMs) into each individual member of a CESM ocean data assimilation ensemble, this study demonstrates that high‐resolution dynamical downscaling can improve model skillfulness at capturing these two events and is thus a potentially useful tool for forecasting extremely high and extremely low precipitation events at subseasonal or even seasonal lead times.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

The remarkable inefficiency of stratocumulus

Marine stratocumulus clouds play a central role in Earth's climate system by reflecting incoming solar radiation and exerting a strong cooling effect. Their organization into open and closed mesoscale cellular morphologies can be thought of as an example of bistable dynamics driven by aerosol–cloud interactions and mesoscale processes. From the perspective of non-equilibrium thermodynamics, these structures are an example of a far-from-equilibrium open system that continuously produces and exports entropy. While entropy production has been studied in idealized deep convective systems, it has not yet been quantified for shallow clouds. Here, we compute and decompose the internal entropy production of open- and closed-cell stratocumulus using an ensemble of large-eddy simulations. We show that the overall entropy production of stratocumulus is low, reflecting the limited vertical extent and corresponding reduced ability to utilize the energy fluxes at the system's boundaries. Moist processes dominate the overall irreversibility, which, combined with their low entropy production, leads to a mechanical efficiency about an order of magnitude smaller than in deep convective systems. Although the dominant irreversible processes differ between open- and closed-cell regimes, the distributions of total entropy production largely overlap across the ensemble, limiting the ability to distinguish the dynamics of individual cases based solely on total entropy production.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Exploring fingerprints of ultrafast structural dynamics in molecular solutions with an X-ray laser

We apply ultrashort x-ray laser pulses to track optically excited structural dynamics of [Ir 2 (dimen) 4 ] 2+ molecules in solution. In our exploratory study we determine angular correlations in the scattered x-rays, which comprise a complex fingerprint of the ultrafast dynamics. Model-assisted analysis of the experimental correlation data allows us to elucidate various aspects of the photoinduced changes in the excited molecular ensembles. We unambiguously identify that in our experiment the photoinduced transition dipole moments in [Ir 2 (dimen) 4 ] 2+ molecules are oriented perpendicular to the Ir-Ir bond. The analysis also shows that the ground state conformer of [Ir 2 (dimen) 4 ] 2+ with a larger Ir–Ir distance is mostly responsible for the formation of the excited state. We also reveal that the ensemble of solute molecules can be characterized with a substantial structural heterogeneity due to solvent influence. In conclusion, the proposed x-ray correlation approach offers an alternative path for studies of ultrafast structural dynamics of molecular ensembles in the liquid and gas phases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Interplay between disorder and collective coherent response: Superradiance and spectral motional narrowing in the time domain

The interplay between static and dynamic disorder and collective optical response in molecular ensembles is an important characteristic of nanoplasmonic and nanophotonic molecular systems. Here we investigate the cooperative superradiant response of a molecular ensemble of quantum emitters under the influence of environmental disorder, including inhomogeneous broadening (as induced by a static random distribution of the molecular transition frequencies) and motional narrowing (as induced by stochastic modulation of these excitation energies). The effect of inhomogeneous broadening is to destroy the coherence of the collective molecular excitation and suppress superradiant emission. However, fast stochastic modulation of the molecular excitation energy can effectively restore the coherence of the quantum emitters and lead to a recovery of superradiant emission, which is an unexpected manifestation of motional narrowing. For a light-scattering process as induced by an off-resonant incident pulse, stochastic modulation leads to inelastic fluorescence emission at the average excitation energy at long times and suggests that dynamic disorder effects can actually lead to collective excitation of the molecular ensemble.

74 ATOMIC AND MOLECULAR PHYSICS↗