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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Automatically generated model for light alkene combustion

Light alkenes are common combustion intermediates for a variety of fuels. Therefore, understanding their oxidation and pyrolysis chemistry is key to building detailed mechanisms for heavier fuels. This work was focused on the development and evaluation of a detailed kinetic mechanism suitable for the combustion of light alkenes up to C 4 without the use of tuned parameters, instead, the parameter values come from first principles or direct measurements. The generated mechanism accurately estimates the laminar burning velocity (S u ) and ignition delay time (IDT) of light alkenes available in the literature, which represent fundamental combustion properties at a wide range of conditions. Because each parameter is thought to have a physically realistic value, not tuned to these measurements, the new model could be used as a sub-mechanism in models for other applications. The reaction network was generated with the open-source Reaction Mechanism Generator (RMG) software. Sensitivity analyses were performed under wide ranges of temperatures and pressures, allowing for the identification of the most impactful species and reactions. Based on these, a comprehensive thermochemistry database, including calculations on 550 molecules performed in this work at the CBS-QB3 level of theory, and a kinetic library, including theoretically-derived reaction rates retrieved from the literature, were built and used in the mechanism generation. The developed mechanism was compared against several existing detailed kinetic mechanisms for ethene, propene, 1-butene, 2-butene, and isobutene. Here, the newly generated model is the most accurate among the ones analyzed, in terms of fractional bias and normalized mean square error. Hence, this new model was used to analyze the chemistry of alkene combustion. Key rate coefficients were compared, to identify the cause of deviations between the models and possible areas for further improvements.

09 BIOMASS FUELS↗
DOE OSTI2021

Colloidal synthesis and charge carrier dynamics of Cs 4 Cd 1-x Cu x Sb 2 Cl 12 (0 ≤ x ≤ 1) layered double perovskite nanocrystals

The toxicity and instability of lead-based metal halide perovskites are the two main obstacles that prevent perovskite materials from implementation in applications. Recently, layered double perovskites (LDPs) emerge as a new family of perovskite materials which provide a new route to solve these problems by lead-component replacement and reduction of crystal structure dimensionality. However, LDP nanocrystals (NCs) have been rarely studied, limiting the further property exploration and application realization. In this work, we report the colloidal synthesis of a series of Cs 4 Cd 1-x Cu x Sb 2 Cl 12 (0 ≤ x ≤ 1) LDP NCs by tuning the stoichiometry of metal precursors. The composition-structure-property relationships of the resulting LDP NCs are studied through materials characterizations, density functional theory calculations, and transient-absorption spectroscopy. In addition, we demonstrate that high-performance high-speed photodetectors can be fabricated using the colloidal LDP NCs through solution-processing. This work premises further expansion of such LDP-based materials for both fundamental studies and application integrations.

25 ENERGY STORAGE↗
DOE OSTI2023

Theory and Simulation of Metal–Insulator–Semiconductor (MIS) Photoelectrodes

A metal–insulator–semiconductor (MIS) structure is an attractive photoelectrode-catalyst architecture for promoting photoelectrochemical reactions, such as the formation of H 2 by proton reduction. The metal catalyzes the generation of H 2 using electrons generated by photon absorption and charge separation in the semiconductor. The insulator layer between the metal and the semiconductor protects the latter element from photo-corrosion and, also, significantly impacts the photovoltage at the metal surface. Understanding how the insulator layer determines the photovoltage and what properties lead to high photovoltages is critical to the development of MIS structures for solar-to-chemical energy conversion. Herein, we present a continuum model for charge-carrier transport from the semiconductor to the metal with an emphasis on mechanisms of charge transport across the insulator. The polarization curves and photovoltages predicted by this model for a Pt/HfO 2 /p-Si MIS structure at different HfO 2 thicknesses agree well with experimentally measured data. The simulations reveal how insulator properties (i.e., thickness and band structure) affect band bending near the semiconductor/insulator interface and how tuning them can lead to operation closer to the maximally attainable photovoltage, the flat-band potential. This phenomenon is understood by considering the change in tunneling resistance with insulator properties. The model shows that the best MIS performance is attained with highly symmetric semiconductor/insulator band offsets (e.g., BeO, MgO, SiO 2 , HfO 2 , or ZrO 2 deposited on Si) and a low to moderate insulator thickness (e.g., between 0.8 and 1.5 nm). Beyond 1.5 nm, the density of filled interfacial trap sites is high and significantly limits the photovoltage and the solar-to-chemical conversion rate. These conclusions are true for photocathodes and photoanodes. This understanding provides critical insight into the phenomena enhancing and limiting photoelectrode performance and how this phenomenon is influenced by insulator properties. The study gives guidance toward the development of next-generation insulators for MIS structures that achieve high performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Addition of P3HT-grafted Silica nanoparticles improves bulk-heterojunction morphology in P3HT-PCBM blends

We present molecular dynamics simulations of a ternary blend of P3HT, PCBM and P3HT-grafted silica nanoparticles (SiNP) for applications in polymer-based solar cells. Using coarse-grained models, we study the effect of SiNP on the spatial arrangement of PCBM in P3HT. Our results suggest that addition of SiNP not only alters the morphology of PCBM clusters but also improves the crystallinity of P3HT. We exploit the property of grafted SiNP to self-assemble into a variety of anisotropic structures and the tendency of PCBM to preferentially adhere to SiNP surface, due to favorable interactions, to achieve morphologies with desirable characteristics for the active layer, including domain size, crystallinity of P3HT, and elimination of isolated islands of PCBM. As the concentration of SiNP increases, the number of isolated PCBM molecules decreases, which in turn improves the crystallinity of P3HT domains. We also observe that by tuning the grafting parameters of SiNP, it is possible to achieve structures ranging from cylindrical to sheets to highly interconnected network of strings. The changes brought about by addition of SiNP shows a promising potential to improve the performance of these materials when used as active layers in organic photovoltaics.

42 ENGINEERING↗
DOE OSTI2016

Graphene-based tunable non-foster circuit for VHF applications

This paper presents a negative impedance converter (NIC) based on graphene field effect transistors (GFETs) for VHF applications. The NIC is designed following Linvill’s open circuit stable (OCS) topology. The DC modelling parameters of GFET are extracted from a device measured by Meric et al. [IEEE Electron Devices Meeting, 23.2.1 (2010)] Estimated parasitics are also taken into account. Simulation results from Keysight Advanced Design System (ADS) show good NIC performance up to 200 MHz and the value of negative capacitance is directly proportional to the capacitive load. In addition, it has been shown that by varying the supply voltage the value of negative capacitance can also be tuned. The NIC stability has been tested up to 2 GHz (10 times the maximum operation frequency) using Nyquist stability criterion to ensure there are no oscillation issues.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2016

Tuning the electronic properties at the surface of BaBiO{sub 3} thin films

The presence of 2D electron gases at surfaces or interfaces in oxide thin films remains a hot topic in condensed matter physics. In particular, BaBiO{sub 3} appears as a very interesting system as it was theoretically proposed that its (001) surface should become metallic if a Bi-termination is achieved (Vildosola et al., PRL 110, 206805 (2013)). Here we report on the preparation by pulsed laser deposition and characterization of BaBiO{sub 3} thin films on silicon. We show that the texture of the films can be tuned by controlling the growth conditions, being possible to stabilize strongly (100)-textured films. We find significant differences on the spectroscopic and transport properties between (100)-textured and non-textured films. We rationalize these experimental results by performing first principles calculations, which indicate the existence of electron doping at the (100) surface. This stabilizes Bi ions in a 3+ state, shortens Bi-O bonds and reduces the electronic band gap, increasing the surface conductivity. Our results emphasize the importance of surface effects on the electronic properties of perovskites, and provide strategies to design novel oxide heterostructures with potential interface-related 2D electron gases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Multi-fidelity modeling to predict the rheological properties of a suspension of fibers using neural networks and Gaussian processes

Unveiling the rheological properties of fiber suspensions is of paramount interest to many industrial applications. There are multiple factors, such as fiber aspect ratio and volume fraction, that play a significant role in altering the rheological behavior of suspensions. Three-dimensional (3D) numerical simulations of coupled differential equations of the suspension of fibers are computationally expensive and time-consuming. Machine learning algorithms can be trained on the available data and make predictions for the cases where no numerical data are available. However, some widely used machine learning surrogates, such as neural networks, require a relatively large training dataset to produce accurate predictions. Multi-fidelity models, which combine high-fidelity data from numerical simulations and less expensive lower fidelity data from resources such as simplified constitutive equations, can pave the way for more accurate predictions. Here, we focus on neural networks and the Gaussian processes with two levels of fidelity, i.e., high and low fidelity networks, to predict the steady-state rheological properties, and compare them to the single-fidelity network. High-fidelity data are obtained from direct numerical simulations based on an immersed boundary method to couple the fluid and solid motion. The low-fidelity data are produced by using constitutive equations. Multiple neural networks and the Gaussian process structures are used for the hyperparameter tuning purpose. Results indicate that with the best choice of hyperparameters, both the multi-fidelity Gaussian processes and neural networks are capable of making predictions with a high level of accuracy with neural networks demonstrating marginally better performance.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

An experimentally informed design process for future inertial confinement fusion facilities

The achievement of ignition in the laboratory has renewed interest in defining the requirements for a future high-gain inertial confinement fusion (ICF) facility. Our best chance of predicting future ICF performance is with 3-D radiation hydrodynamic simulations that have been benchmarked against experimental data, but their high computational cost is prohibitive for use in practical design studies. We introduce a hierarchical approach where 3-D simulations are tuned to match experimental measurements and used to train 3-D degradation models in 1-D simulations allowing for accurate predictions over the entire OMEGA direct-drive database. A genetic algorithm was used in combination with the trained 1-D simulations to search for optimal direct-drive implosion designs at driver energies ranging from 20 kJ to 10 MJ. As the fidelity of 3-D codes improves, this approach will provide a viable experimentally informed tool for defining the next ICF facility.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

An Artificial Retina Processor for Track Reconstruction at the LHC Crossing Rate

The goal of the INFN-RETINA R&D project is to develop and implement a computational methodology that allows to reconstruct events with a large number (> 100) of charged-particle tracks in pixel and silicon strip detectors at 40 MHz, thus matching the requirements for processing LHC events at the full bunch-crossing frequency. Our approach relies on a parallel pattern-recognition algorithm, dubbed artificial retina, inspired by the early stages of image processing by the brain. In order to demonstrate that a track-processing system based on this algorithm is feasible, we built a sizable prototype of a tracking processor tuned to 3 000 patterns, based on already existing readout boards equipped with Altera Stratix III FPGAs. The detailed geometry and charged-particle activity of a large tracking detector currently in operation are used to assess its performances. We report on the test results with such a prototype.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Effect of heat treatment paths on the aging and rejuvenation of metallic glasses

Here, this study explores the influence of heat treatment paths on the structural relaxation of metallic glasses (MGs) in the regime of fast dynamics. We create MG samples using various quenching rates, from 10 9 to 10 11 K/s, and expose these samples to near-T g heat treatments with assorted combinations of heating/cooling rates, from 5×10 10 to 5×10 12 K/s, and annealing durations, from 10 ps to 10 ns. Results show that the effect of the heating rate is intricately tied to the initial structure of the MG, while a decrease in the cooling rate invariably intensifies the aging process. Extending the annealing duration may induce either aging or rejuvenation, subject to the specific thermal history. To interpret these findings, we hypothesize that the memory effect, governed by the activation and annihilation of reversible and irreversible flow units, underpins the rejuvenation-aging competition in MGs. Moreover, we suggest viewing the cooling stage as an annealing phase controlled by gradient temperature and fine-tuning its rate to achieve the targeted active flow unit distributions. This study illuminates the role of fast dynamics during the glass relaxation process and offers practical strategies for tailoring heat treatments to optimize MG structures and mechanical performance.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Parton showers and matching uncertainties in top quark pair production with Herwig 7

Abstract We evaluate the theoretical uncertainties in next-to-leading order plus parton shower predictions for top quark pair production and decay in hadronic collisions. Our work is carried out using the Herwig 7 event generator and presents an in-depth study of variations in matching schemes with two systematically different shower algorithms, the traditional angular-ordered and alternative dipole shower. We also present all of the required extensions of the Herwig dipole shower algorithm to properly take into account quark mass effects, as well as its ability to perform top quark decays. The predictions are compared at parton level as well as to Large Hadron Collider data, including in the boosted regime. We find that the regions where predictions with a non-top-quark-specific tune differ drastically from data are plagued by large uncertainties which are consistent between our two shower and matching algorithms.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

From Rules to Reasoning: A Survey of Large Language Model-Based Approaches to Scientific Hypothesis and Idea Generation

Scientific hypothesis generation represents a fundamental challenge in contemporary research due to exponentially expanding literature volumes and increasing disciplinary specialization. Large language models (LLMs) have emerged as transformative tools for automated scientific discovery, moving beyond traditional rule-based and literature-mining approaches. Four paradigmatic approaches define current LLM-driven hypothesis generation: direct prompting and fine-tuning methods, knowledge-enhanced frameworks integrating retrieval-augmented generation (RAG), multi-agent collaborative systems simulating research teams, and reasoning-focused approaches implementing cognitive architectures. Domain-specific applications demonstrate statistical equivalence to human expert performance in social psychology, experimental validation in biomedical research, and near-expert quality in astronomy. Evaluation methodologies encompass human expert assessment, LLM-as-judge frameworks, and comprehensive benchmarking systems. Technical challenges include hallucination management, knowledge integration limitations, and balancing novelty with feasibility. Future directions emphasize hybrid neural-symbolic architectures and sophisticated human-AI collaboration models for responsible scientific discovery acceleration.

AI-driven discovery↗
DOE OSTI2023

Modeling Nanoscale Ohmics in Carbon Supports of Fuel Cell Cathodes

Here, reducing platinum (Pt) loading in polymer electrolyte fuel cells (PEFCs) while meeting performace requirements is critical to their widespread deployment. However, significant polarization losses manifest at higher current densities in cathodes with lower Pt content. The morphology of the carbon supports in PEFC cathodes affects the location of Pt deposition into the micropits or onto the surface of the carbon support, translating into different kinetic and transport resistances. In this work, we derive an agglomerate scale model that differentiates the sink terms for Pt on the surface and in the pits of carbon supports. We develop an approach to assess the impact of nanoscale ohmic resistance to Pt in the micropits arising from weakly ionic solution in the carbon support on PEFC performance. Effectiveness factors relating the actual reaction rate to the maximum reaction rate (had all the Pt been exposed) are derived and embedded into a one-dimensional catalyst layer model. Parameters in the catalyst layer model are tuned based on experimental local oxygen transport resistances. Subsequently, we estimate bounds for the micropore resistances based on geometric and physical arguments. Lastly, polarization curves are simulated to assess the effect of the micropore resistance in fully-humidified and oxygen-rich environments.

25 ENERGY STORAGE↗
DOE OSTI2019

High Conductivity and Flexible Hybrid Solid State Electrolyte (Final Report: DOE-EE0007807)

The project objective is to develop flexible hybrid electrolyte with garnet nanofibers to achieve the following: (1) flexible, with greater mechanical strength (~ 10 MPa) and thermal stability than polymer electrolytes; (2) high room-temperature ionic conductivity, ~ 0.5 mS/cm; (3) stable interface with lithium metal and effective blocking of lithium dendrites at current densities up to 3 mA/cm 2 ; and (4) battery performance with Li S chemistry with an energy density of ≥ 450 Wh/kg (and ≥ 1000 Wh/L) and maintaining ≥ 80% of capacity up to 500 cycles. We synthesized garnet nanofibers, filled the porous region with polymer electrolyte, and characterized and tuned the flexible hybrid membrane properties. The flexible hybrid SSE microstructure was analyzed by leveraging the UMD AIMLab Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) tools and integrated with electrochemical methods at the UMERC Battery Fabrication Lab to investigate the properties and stability with Li metal anode. We developed a fundamental understanding of the mechanism of Li ionic diffusion in garnet nanofibers and their mechanical properties, as well as these properties for hybrid garnet-fiber/polymer hybrids. Work progressed toward the study of the electrode assembly during electrochemical cycling of the anode.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Spot Size Optimization of the Scorpius Accelerator

The Scorpius Linear Induction Accelerator (LIA) is being developed by the Advanced Sources and Diagnostics (ASD) Project and will complement other U1a capabilities by providing a multi-pulse, DARHT-class, flash-radiography capability. Commissioning activities are expected to end in Spring of 2026. All of the diagnostics discussed in this chapter are relevant to LIAs that generate high-current relativistic electron beams, and some diagnostics will also be relevant to other accelerators. The Scorpius Accelerator will be the world’s most advance LIA. Although significant technological advancements have been incorporated throughout the machine, many performance aspects of Scorpius will be similar to those of FXR and DARHT Axis-I and -II. These LIAs offer the same challenges, whether it is suppressing beam instabilities, improving diagnostic accuracy, validating computer simulations and beam tunes, or reducing beam-target interaction effects. However, the ultimate figure of merit is consistent between these LIAs, which is spot size and dose.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Tunable anisotropy of co-based nanocomposites for magnetic field sensing and inductor applications

A method includes producing an amorphous precursor to a nanocomposite, performing devitrification of the amorphous precursor, forming, based on the devitrification, the nanocomposite comprising an induced magnetic anisotropy, and for a first portion of the nanocomposite, determining a desired value of a magnetic permeability of the first portion, tuning, based on the desired value, the induced magnetic anisotropy for the first portion, and adjusting, based on the tuning of the induced magnetic anisotropy of the first portion, a first magnetic permeability value of the first portion of the nanocomposite, wherein the first magnetic permeability value is different from a second magnetic permeability value for a second portion of the nanocomposite.

Leary, Alex M.↗
DOE OSTI2021

Exploring the structural uniformity and integrity of protonic ceramic thin film electrolyte using wet powder spraying

Thin protonic ceramic electrolyte contributes to lower ohmic resistance and enhances electrochemical performance of protonic ceramic electrochemical cells. However, manufacturing of large-scale thin electrolyte remains a challenge. Wet powder spraying is an attractive technique to deposit <10 µm thin electrolyte when advanced atomizing techniques and optimized spraying process are integrated. Here ultrasonic atomization is integrated in the wet powder spray technique to reduce the thickness of electrolyte. Moreover, a parametric study is conducted to optimize the wet powder spray process to deposit uniform and crack-free electrolyte film. It is illustrated that tuning of solid loading rates and spray passes can affect the morphology of the as-sprayed electrolyte film, enabling the structural compactness of the sintered electrolyte layer. To maintain chemical stability of the electrolyte layer during sintering, effect of sintering temperature is further investigated to produce a physically thin, structurally dense, and chemically homogeneous electrolyte layer. The protonic ceramic electrochemical cells fabricated with optimized spraying and sintering parameters demonstrate excellent performance under both fuel cell and electrolysis modes. In addition, the cells exhibit remarkable structural integrity during redox and long-term stability tests.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Predicting Excitation Energies of Twisted Intramolecular Charge-Transfer States with the Time-Dependent Density Functional Theory: Comparison with Experimental Measurements in the Gas Phase and Solvents Ranging from Hexanes to Acetonitrile

Electronically excited states characterized by intramolecular charge transfer play an essential role in many biological processes and optical devices. The ability to make quantitative ab initio predictions of the relative energetics involved is a challenging yet desirable goal, especially for large molecules in solution. In this work, we present a data set of 61 experimental measurements of absorption and emission processes, both in the gas phase and in solvents representing a broad range of polarities, which involve intramolecular charge transfer mediated by a nonzero, "twisted" dihedral angle between one or more donor and acceptor subunits. Among a variety of density functionals investigated within the framework of linear-response theory, the "optimally tuned" LRC-ωPBE functional, which utilizes a system-specific yet nonempirical procedure to specify the range-separation parameter, emerges as the preferred choice. For the entire set of excitation energies, involving changes in dipole moment ranging from 4 to >20 Debye, the mean signed and absolute errors are 0.02 and 0.18 eV, respectively (compared, e.g., to -0.30 and 0.30 for PBE0, 0.44 and 0.47 for LRC-ωPBEh, 0.83 and 0.83 for ωB97X-V). We analyze the performance of polarizable continuum solvation models available in Q-Chem that partition the solvent response into fast and slow time scales, and clear trends emerge when measurements corresponding to the four small 4-(dimethylamino)benzonitrile (DMABN)-like molecules and a charged species are excluded. We make the case that the large errors found only for small molecules in the gas phase and weak solvents cannot be expected to improve via the optimal tuning procedure, which enforces a condition that is exact only in the well-separated donor-acceptor limit, and present empirical evidence implicating the outsized importance for small donor-acceptor systems of relaxation effects that cannot be accounted for by the linear-response time-dependent density functional theory within the adiabatic approximation. Finally, we demonstrate the utility of the optimally tuned density functional approach by targeting the charge-transfer states of a large biomimetic model system for light-harvesting structures in Photosystem II.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

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