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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Autonomous alloy composition optimization using molecular dynamics guided by a large language model

Here, we present an autonomous materials discovery framework that couples a large language model (LLM) with molecular dynamics (MD) simulations to optimize Fe–Cr–Mn alloy compositions for tensile strength. Starting from six distinct compositions, the LLM operated as an intelligent agent, iteratively proposing changes based on prior simulation results and constraints. Over 50 iterations per case, the LLM adaptively explored the composition space, identifying high-strength regions, not easily accessible by conventional methods. The highest strength, 18.7 GPa, was achieved with Fe 71 Cr 25 Mn 4 composition, identified from a Fe 75 Cr 20 Mn 5 starting point. The LLM autonomously adjusted its strategy in real time, demonstrating closed-loop decision-making using commodity hardware. This approach showcases the potential of LLMs as scientific co-pilots, capable of accelerating materials discovery and generalizable to other domains like biology and drug design.

Autonomy↗
DOE OSTI2021

How Many Trip Requests Could We Support? An Activity-Travel Based Vehicle Scheduling Approach

In a world of ever-changing travel behavior and ever-increasing modal options, is vital to have integrated models that could capture the interactions between supply and demand layers of travel. Addressing this need, we propose three different versions of network representation and mathematical models for the activity-based vehicle routing problem to connect activity-travel graphs of passengers (demand layer) to spatio-temporal networks of vehicles (supply layer). Versions I and II are arc-based, while version III is path-based. In version I, we introduce the concept of activity-travel graphs for passengers. For vehicles, we construct space–time networks and add a new dimension, called “under-service state”, to track the execution status of trip requests at any location and time. In version II, we reduce the complexity of the network structure by eliminating the state dimension and some other modifications in the structure of the passengers’ and vehicles’ network. Although both versions can capture various behavioral constraints of the activity-based vehicle routing problem (e.g., mandatory and optimal activities, duration of activities, chain of activities, preferred starting and ending times of activities), due to the high level of complexity of the network structure, both versions can only solve small-sized problems. To tackle the computational complexity, we propose a path-based network representation in version III, and to make a balance between the disutility of passengers and vehicles, we present a tolled user equilibrium problem. Mathematical models are coded in C and GAMS and implemented on real-world Phoenix regional transportation network with more than 39 million trip requests, which demonstrate the effectiveness of the proposed solution for the original and restricted master problems.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

AutonomieAI: An efficient and deployable vehicle energy consumption estimation toolkit

Here, this paper presents AutonomieAI, a novel toolkit designed for efficient energy estimation of vehicles across diverse trip scenarios, routes, and drive cycles, applicable to a broad range of vehicle powertrain technologies. It leverages state-of-the-art Machine Learning techniques to deliver real-time energy prediction of vehicles, enabling co-simulation with transportation level system tools and opening doors for large-scale optimization at city, network or national level. Benchmark results show that AutonomieAI achieves high accuracy, with an average percentage error below 2% for most powertrain types, and computational efficiency capable of processing over 10,000 trips per second. Applications of AutonomieAI have potential to offer the flexibility to assist in solving eco-routing problems, optimize for vehicle and powertrain selection, study charging decision behavior, and optimize for charging station placement. AutonomieAI is the result of large neural network based model architectures, trained on very large and unique high fidelity vehicle simulation data. It is lightweight, deployable, efficient and has accuracy comparable to specialized and complex physics based simulation softwares.

Autonomie↗
DOE OSTI2023

Meeting report: The first soil viral workshop 2022

Soil viral ecology is a growing research field; however, the state of knowledge still lags behind that of aquatic systems. Therefore, to facilitate progress, the first Soil Viral Workshop was held to encourage international scientific discussion and collaboration, suggest guidelines for future research, and establish soil viral research as a concrete research area. The workshop took place at Søminestationen, Denmark, between 15 and 17th of June 2022. The meeting was primarily held in person, but the sessions were also streamed online. The workshop was attended by 23 researchers from ten different countries and from a wide range of subfields and career stages. Eleven talks were presented, followed by discussions revolving around three major topics: viral genomics, virus-host interactions, and viruses in the soil food web. The main take-home messages and suggestions from the discussions are summarized in this report.

09 BIOMASS FUELS↗
DOE OSTI2022

Correlated mechanochemical maps of Arabidopsis thaliana primary cell walls using atomic force microscope infrared spectroscopy

Spatial heterogeneity in composition and organisation of the primary cell wall affects the mechanics of cellular morphogenesis. However, directly correlating cell wall composition, organisation and mechanics has been challenging. To overcome this barrier, we applied atomic force microscopy coupled with infrared (AFM-IR) spectroscopy to generate spatially correlated maps of chemical and mechanical properties for paraformaldehyde-fixed, intact Arabidopsis thaliana epidermal cell walls. AFM-IR spectra were deconvoluted by non-negative matrix factorisation (NMF) into a linear combination of IR spectral factors representing sets of chemical groups comprising different cell wall components. This approach enables quantification of chemical composition from IR spectral signatures and visualisation of chemical heterogeneity at nanometer resolution. Cross-correlation analysis of the spatial distribution of NMFs and mechanical properties suggests that the carbohydrate composition of cell wall junctions correlates with increased local stiffness. Together, our work establishes new methodology to use AFM-IR for the mechanochemical analysis of intact plant primary cell walls.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Unitary quantum lattice simulations for Maxwell equations in vacuum and in dielectric media

Utilizing the similarity between the spinor representation of the Dirac and the Maxwell equations that has been recognized since the early days of relativistic quantum mechanics, a quantum lattice algorithm (QLA) representation of unitary collision-stream operators of Maxwell's equations is derived for both homogeneous and inhomogeneous media. A second-order accurate 4-spinor scheme is developed and tested successfully for two-dimensional (2-D) propagation of a Gaussian pulse in a uniform medium whereas for normal (1-D) incidence of an electromagnetic Gaussian wave packet onto a dielectric interface requires 8-component spinors because of the coupling between the two electromagnetic polarizations. In particular, the well-known phase change, field amplitudes and profile widths are recovered by the QLA asymptotic profiles without the imposition of electromagnetic boundary conditions at the interface. The QLA simulations yield the time-dependent electromagnetic fields as the wave packet enters and straddles the dielectric boundary. QLA involves unitary interleaved non-commuting collision and streaming operators that can be coded onto a quantum computer: the non-commutation being the very reason why one perturbatively recovers the Maxwell equations.

Physics↗
DOE OSTI2021

Scattering of radiofrequency waves by randomly modulated density interfaces in the edge of fusion plasmas

In the scrape-off layer and the edge region of a tokamak, the plasma is strongly turbulent and scatters the radiofrequency (RF) electromagnetic waves that propagate through this region. It is important to know the spectral properties of these scattered RF waves, whether used for diagnostics or for heating and current drive. The spectral changes influence the interpretation of the obtained diagnostic data, and the current and heating profiles. A full-wave, three-dimensional (3-D) electromagnetic code ScaRF has been developed for studying the RF wave propagation through turbulent plasma. ScaRF is a finite-difference frequency-domain (FDFD) method used for solving Maxwell's equations. The magnetized plasma is defined through the cold plasma by the anisotropic permittivity tensor. As a result, ScaRF can be used to study the scattering of any cold plasma RF wave. It can also be used for the study of the scattering of electron cyclotron waves in ITER-type and medium-sized tokamaks such as TCV, ASDEX-U and DIII-D. For the case of medium-sized tokamaks, there is experimental evidence that drift waves and rippling modes are present in the edge region. Hence, we have studied the scattering of RF waves by periodic density interfaces (plasma gratings) in the form of a superposition of spatial modes with varying periodicity and random amplitudes. The power reflection coefficient (a random variable) is calculated for different realizations of the density interface. In this work, the uncertainty of the power reflection coefficient is rigorously quantified by use of the Polynomial Chaos Expansion method in conjunction with the Smolyak sparse-grid integration, which is known as the PCE-SG method. The PCE-SG method is proven to be accurate and more efficient compared with alternative methods such as the Monte Carlo (MC) approach.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

A hybrid full-wave Markov chain approach to calculating radio-frequency wave scattering from scrape-off layer filaments

The interaction of radio-frequency (RF) waves with edge turbulence modifies the incident wave spectrum, and can significantly affect RF heating and current drive in tokamaks. Previous lower hybrid (LH) scattering models have either used the weak-turbulence approximation, or treated more realistic, filamentary turbulence in the ray tracing limit. In this study, a new model is introduced which retains full-wave effects of RF scattering in filamentary turbulence. First, a Mie-scattering technique models the interaction of an incident wave with a single Gaussian filament. Next, an effective differential scattering width is derived for a statistical ensemble of filaments. Lastly, a Markov chain solves for the transmitted wave spectrum in slab geometry. This model is applied to LH launching for current drive. The resulting wave spectrum is asymmetrically broadened in angular wavenumber space. This asymmetry is not accounted for in previous LH scattering models. The modified wave spectrum is coupled to a ray tracing/Fokker–Planck solver (GENRAY/CQL3D) to study its impact on current drive. The resulting current profile is greatly altered, and there is significant increase in the on-axis current and decrease in the off-axis peaks. This is attributed to a portion of the modified wave spectrum that is strongly dampened on-axis during the first pass.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Chemistry, Structure, and Function of Lone Pairs in Extended Solids

The lone pair has been a known feature of the electronic structure of molecules for over 100 years. Beginning with the pioneering work of Lewis and others that was later developed into useful guidelines for predicting molecular structure, lone pairs and their steric consequences are now taught at the very earliest stages of a chemistry education. In the crystalline solid state, lone pairs have perhaps had a less visible yet equally consequential role, with a significant impact on a range of properties and functionalities. Important properties associated with s 2 electron-derived lone pairs include their role in creating conditions favorable for ion transport, in the formation and correlation of local dipoles and the resulting polar behavior leading to ferroics and multiferroics, in increasing the refractive index of glass, in reducing the thermal conductivity of thermoelectric materials, and in breaking local symmetry permitting second-harmonic light generation.. In recent years, the role of the lone pair in developing the electronic structure of some topological quantum materials has also been recognized. While structural distortions due to lone pairs have traditionally been characterized through their crystallography, recent advances in scattering and spectroscopy have revealed the presence of local lone pair-driven distortions that do not correlate over long length scales. The role of these crystallographically “hidden” lone pairs, their detection, and their impact on properties have become a growing body of work in the literature. Hidden lone pairs are an effective argument for considering a role for lone pairs that goes beyond their being objects that occupy space in the coordination polyhedra of cations. This Account introduces the chemistry of lone pairs in extended crystalline solids, including a discussion of when they are stereochemically active, how they manifest in the structure, and how their chemistry can be tuned by the chemical environment around them. Eventually, all of these factors work in unison to help develop and tune properties of interest. Certain specific examples of structure–property relationships in materials that are driven by lone pair behavior are described here, including the potential impact of lone pairs on the optical and electronic properties of hybrid halide perovskite compounds that are relevant to their photovoltaic applications. Here, we highlight the role of lone pairs in the dielectric behavior of geometrically frustrated pyrochlores, the temperature-dependent optoelectronic behavior of halide perovskites, the polar phase transitions in lead-free ferroelectric perovskites, and the compositional insulator-to-metal transition in ruthenium pyrochlores. The theme underpinning this Account is that the lone pair can be considered to be a powerful design element for a broad range of material function.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Growth-Controlled Broad Emission in Phase-Pure Two-Dimensional Hybrid Perovskite Films

Two-dimensional hybrid metal halide perovskites (2D perovskites) are attractive for light-emitting devices and other applications because their emission is tunable across the visible spectrum. The emission profile of 2D perovskites can be broadened via a variety of mechanisms and is further complicated by the presence of impurities. Here, the challenge of making phase-pure films in Ruddlesden–Popper phases [(A') 2 (A) n–1 B n X 3n+1 structure] is overcome by using a single A/A'-site cation, ethylammonium (EA), whose optimal size also prohibits the formation of off-target phases. In the (EA) 2 (EA) n–1 Pb n Br 3n+1 family, the low-energy, broad emission observed in bulk crystals is reduced in spin-cast, polycrystalline films. This decrease in broad emission, attributed to phonon-mediated processes, is correlated with the strain in polycrystalline films that is observed by X-ray scattering. Photothermal deflection spectroscopy shows that strain also increases the electronic disorder near the free exciton absorbance. Broad emission in films can be recovered by slowing growth kinetics, which removes the strain acquired from spin-casting and increases the domain size. Furthermore, these results help extend the utility of 2D perovskites by suggesting design rules for the growth of thin films with the targeted phase and emission.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Ligand Control of Structural Diversity in Luminescent Hybrid Copper(I) Iodides

Copper(I) iodide hybrids are of interest for next-generation lighting technologies because of their efficient luminescence in the absence of rare-earth elements. Here, we report 10 structurally diverse hybrid copper(I) iodides that emit in the green–red region with quantum yields reaching 67%. The compounds display a diversity of structures including ones with one-dimensional (1D) Cu–1 chains, Cu 2 I 2 rhomboid dimers, and structures with two different arrangements of Cu 4 I 4 tetramers. The compounds with Cu 2 I 2 rhomboid dimers or Cu 4 I 4 cubane tetramers have higher photoluminescence quantum yields than those with Cu–I 1D chains and octahedral Cu 4 I 4 tetramers, owing to the optimal degree of condensation of the inorganic motifs, which suppresses nonradiative processes. Electronic structure calculations on these compounds point out the critical influence of the inorganic motif and organic ligand on the nature of the band gaps and thus the excitation characteristics. Temperature-dependent photoluminescence spectra are presented to better understand the nature of luminescence in compounds with different inorganic motifs. Here. the emerging understanding of composition–structure–property correlations in this family provides inspiration for the rational design of hybrid phosphors for general lighting applications.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Electrochemical Control of Magnetism on the Breathing Kagome Network of Li x ScMo 3 O 8

Controlling properties within a given functional inorganic material structure type is often accomplished through tuning the electronic occupation, which is in turn dictated by the elemental composition determined at the time of material preparation. We employ electrochemical control of the lithium content, with associated electronic occupancy control, to vary the magnetic properties of a material where a kagome-derived network of Mo 3 triangles carry the spin. In this case, Li is electrochemically inserted into LiScMo 3 O 8 , a layered compound containing a breathing Mo kagome network. Up to two additional Li can be inserted into LiScMo 3 O 8 , transforming it into Li 3 ScMo 3 O 8 . Li 2 ScMo 3 O 8 prepared by electrochemical lithiation is compared to the quantum spin liquid candidate compound Li 2 ScMo 3 O 8 prepared through high-temperature solid-state methods, which has a slightly different structural stacking sequence but a similar kagome-derived network. Magnetic measurements are supported by first-principles calculations, showing that electrons remain localized on the Mo clusters throughout the doping series. As x is varied in Li x ScMo 3 O 8 , the measurements and calculations reveal the evolution from a diamagnetic band insulator at x = 1 to a geometrically frustrated magnet at x = 2, back to a diamagnetic insulator at x = 3. These results indicate a likelihood of strong coupling between the degree of Li disorder and charge/magnetic ordering over the Mo 3 clusters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗