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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 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 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 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↗
DOE OSTI2023

Tuning the Mobility of Indacenodithiophene-Based Conjugated Polymers via Coplanar Backbone Engineering

Conjugated polymers based on indacenodithiophene-benzothiadiazole (IDT-BT) have attracted great interest due to their high charge carrier mobilities while being low crystallinity (i.e. near-amorphous.) They represent a promising design strategy to achieve both excellent stretchability and electrical performance. Here, we describe an approach on structural modifications of IDT-BT, namely by introducing non-covalent interactions and substituting building blocks to promote extended coplanar backbones. We systematically investigated the effects of structural modifications on backbone conformation, polymer aggregations, and charge carrier mobilities. Among the investigated polymers, the fluorinated derivative IDT-FBT demonstrated the highest charge carrier mobility of 5.19 cm 2 /Vs, along with low activation energy and Urbach energy indicating its low energy disorder level. The high mobility was attributed to the higher backbone planarity reinforced by S···F and H···F non-covalent interactions and improved interchain interactions through strong aggregation. In conclusion, our findings indicate that increasing backbone coplanarity may further improve mobility in low crystallinity conjugated polymers.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Enabling Magnesium Anodes by Tuning the Electrode/Electrolyte Interfacial Structure

Here, a new deposition mechanism is presented in this study to achieve highly reversible plating and stripping of magnesium (Mg) anodes for Mg-ion batteries. It is known that the reduction of electrolyte anions such as bi s (trifluoromethanesulfonyl) imide (TFSI - ) causes Mg surface passivation, resulting in poor electrochemical performance for Mg-ion batteries. We reveal that the addition of sodium cations (Na + ) in Mg-ion electrolytes can fundamentally alter the interfacial chemistry and structure at the Mg anode surface. The molecular dynamics simulation suggests that Na + cations contribute to a significant population in the interfacial double layer so that TFSI - anions are excluded from the immediate interface adjacent to the Mg anode. As a result, the TFSI - decomposition is largely suppressed so does the formation of passivation layers at the Mg surface. This mechanism is supported by our electrochemical, microscopic, and spectroscopic analyses. The resultant Mg deposition demonstrates smooth surface morphology and lowered overpotential compared to the pure Mg(TFSI) 2 electrolyte.

25 ENERGY STORAGE↗
DOE OSTI2025

Calibration and Performance of the ICARUS Detector at Fermilab

ICARUS is the largest Liquid Argon Time Projection Chamber (LArTPC) in operation and serves as the Far Detector of the Short Baseline Neutrino (SBN) program at Fermilab. Precise detector calibration is essential for reliable energy reconstruction and for maximizing the physics reach of the experiment. In this talk, I will describe the energy and timing calibration procedures developed at ICARUS. Thanks to the abundant flux of cosmic ray muons at the surface, the TPC response to ionization charge has been equalized across the detector, removing non-uniformities and in-transparency effects. A novel data-driven procedure has been used to tune the simulation of ionization signals and electronics noise yielding close agreement between Monte Carlo and data with minimal residual bias in reconstructed charge. In addition, the light detection system has been calibrated to sub-nanosecond timing resolution. This precision enables efficient cosmic background rejection and accurate synchronization of neutrino interactions with the time structure of both the Booster Neutrino Beam (BNB) and Neutrinos at the Main Injector (NuMI) beam. Together, these efforts demonstrate the robust performance of the detector and provide critical experience for future large LArTPCs, such as DUNE.

Vicenzi, Matteo [Brookhaven]↗
DOE OSTI2025

Repurposing Post-Consumer Polyethylene to Access Cross-Linked Polyethylene with Reprocessabilty, Recyclability, and Tunable Properties

Polyethylene (PE) is the most widely produced plastic but accumulation and resistance to degradation has significantly contributed to the plastic waste crisis. Upcycling has presented promising solutions to transform PE waste into value-added products. In this study, mixed post-consumer PE was successfully repurposed into reprocessable and chemically recyclable cross-linked polyethylene (XLPE). This process involved converting PE into telechelic oligomers, followed by repolymerization using a hybrid cross-linking system consisting of a dynamic cross-linker 2,4,6-triethoxy-1,3,5-triazine (TETA) and non-dynamic cross-linker tris(6-isocyanatohexyl)isocyanurate (Tri-HDI). In the resulting XLPE, TETA facilitated iterative reprocessing with minimal property degradation across cycles, whereas Tri-HDI helped preserve functional performance throughout service life. Compared to PE, XLPE exhibited enhanced mechanical properties, reduced creep deformation under application-relevant temperatures, and high temperature structural stability. Notably, copolymerizing PE oligomers with commercial macrodiols was employed to create composite XLPEs, enabling tuning material properties. After use, XLPE can be efficiently and selectively depolymerized under mild conditions, even when mixed with commercial insulator cables. This depolymerization allows for the recovery of the constituent building blocks, enabling purification and subsequent repolymerization for reuse. This approach demonstrates the potential of repurposing plastic waste into sustainable materials and fostering the development of a circular economy.

INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMI↗
DOE OSTI2020

Selective hydrogenation of CO 2 and CO over potassium promoted Co/ZSM-5

The utilization of CO 2 as a C 1 feedstock for synthesis of value-added chemicals and fuels could both mitigate the negative effects associated with increasing CO 2 emissions and decrease dependence on fossil fuels as part of a future circular carbon economy. Co-based catalysts have been well-developed for Fischer-Tropsch synthesis (FTS), but replacing the CO reactant with CO 2 (CO 2 -FTS) typically results in low selectivity toward desirable light olefins. To better understand the structure-property relationships of Co-based catalysts, and extend promising FTS results to CO 2 -FTS, we have studied the effect of a potassium promoter and acidic properties of ZSM-5 on catalytic performance. The selectivity of FTS and CO 2 -FTS is shown to be a strong function of Si/Al ratio in co-impregnated catalysts, with findings supported by in situ XAFS and FTIR, demonstrating light olefin selectivity can be tuned by Si/Al ratio and the method of introducing the K promoter.

36 MATERIALS SCIENCE↗