Search NASA⌕ Search

SEARCH · Search NASA

Results for “computational spectroscopy”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

NASA’s Pandora SmallSat Mission: Simulating the Impact of Stellar Photospheric Heterogeneity and Its Correction

Stellar photospheric heterogeneity is a dominant astrophysical systematic impacting exoplanet transmission spectroscopy. NASA’s Pandora SmallSat Mission is designed to address this challenge through contemporaneous visible-band photometry and near-infrared spectroscopy of exoplanet host stars. Here, we present an end-to-end simulation study quantifying Pandora’s ability to infer stellar photospheric properties and correct stellar contamination using out-of-transit observations. We construct eight representative stellar activity scenarios and generate 160 simulated Pandora datasets, incorporating time-dependent stellar spectra, instrument response, and noise. Given accurate models, Bayesian retrievals of joint visible photometry (0.4–0.7 μm) and near-infrared spectroscopy (0.9–1.6 μm, R ≈ 120) recover photospheric temperatures with typical uncertainties of ≈30 K, with no significant bias. Models with two spectral components (i.e., a quiescent photosphere and spots) are strongly favored in 95% of cases; one-component models are preferred when true spot filling factors fall below a detection threshold of ≈0.3%. We propagate the true and inferred stellar parameters to compute true, inferred, and residual contamination signals under physically motivated spot geometries. For simple spot distributions, contamination signals of 10 2 –10 3 ppm are reduced to ≲10 ppm—well below Pandora’s expected transmission spectroscopy precision (30–100 ppm). For more complex spot distributions, geometric degeneracies limit deterministic corrections, leaving residual contamination at the 10 3 ppm level that must be mitigated using additional constraints, such as spot-crossing events and joint stellar–planetary retrievals of transmission spectra. These results define regimes in which stellar contamination can be corrected from stellar observations alone and show how Pandora stellar observations can identify cases where additional information is required.

Astronomy and AstroPhysics↗
DOE OSTI2025

First-Principles Statistical Mechanics Study of Magnetic Fluctuations and Order–Disorder in the Spinel LiNi 0.5 Mn 1.5 O 4 Cathode

While significant magnetic interactions exist in lithium transition metal oxides, commonly used as Li-ion cathodes, the interplay between magnetic couplings, disorder, and redox processes remains poorly understood. In this work, we focus on the high-voltage spinel LiNi 0.5 Mn 1.5 O 4 (LNMO) cathode as a model system on which to apply a computational framework that uses first principles-based statistical mechanics methods to predict the finite temperature magnetic properties of materials and provide insights into the complex interplay between magnetic and chemical degrees of freedom. Density functional theory calculations on multiple distinct Ni–Mn orderings within the LNMO system, including the ordered ground-state structure (space group P4332), reveal a preference for a ferrimagnetic arrangement of the Ni and Mn sublattices due to strong antiferromagnetic superexchange interactions between neighboring Mn 4+ and Ni 2+ ions and ferromagnetic Mn–Mn and Ni–Ni couplings, as revealed by magnetic cluster expansions. These results are consistent with qualitative predictions using the Goodenough-Kanamori-Anderson rules. Simulations of the finite temperature magnetic properties of LNMO are conducted using Metropolis Monte Carlo. We find that a “semiclassical” Monte Carlo sampling method based on the Heisenberg Hamiltonian accurately predicts experimental magnetic transition temperatures observed in magnetometry measurements. This study highlights the importance of a robust computational toolkit that accurately captures the complex chemomagnetic interactions and predicts finite temperature magnetic behavior to help analyze experimental magnetic and magnetic resonance spectroscopy data acquired ex situ and operando.

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

Dynamic mode decomposition of nonequilibrium electron-phonon dynamics: accelerating the first-principles real-time Boltzmann equation

Abstract Nonequilibrium dynamics governed by electron–phonon ( e -ph) interactions plays a key role in electronic devices and spectroscopies and is central to understanding electronic excitations in materials. The real-time Boltzmann transport equation (rt-BTE) with collision processes computed from first principles can describe the coupled dynamics of electrons and atomic vibrations (phonons). Yet, a bottleneck of these simulations is the calculation of e –ph scattering integrals on dense momentum grids at each time step. Here we show a data-driven approach based on dynamic mode decomposition (DMD) that can accelerate the time propagation of the rt-BTE and identify dominant electronic processes. We apply this approach to two case studies, high-field charge transport and ultrafast excited electron relaxation. In both cases, simulating only a short time window of ~10% of the dynamics suffices to predict the dynamics from initial excitation to steady state using DMD extrapolation. Analysis of the momentum-space modes extracted from DMD sheds light on the microscopic mechanisms governing electron relaxation to a steady state or equilibrium. The combination of accuracy and efficiency makes our DMD-based method a valuable tool for investigating ultrafast dynamics in a wide range of materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Simulating topological quantum gates in two-dimensional magnet-superconductor hybrid structures

The creation of topological quantum gates using Majorana zero modes—an outstanding problem in the field of topological quantum computing—relies on our ability to control the braiding process in time and space. Here, we propose two-dimensional magnet-superconductor hybrid structures as a new platformfor the successful implementation of topologically protected √σ z -, σ z - and σ x -quantum gates using Majorana zero modes. Employing a novel theoretical formalism to compute the full timedependent many-body wave-function and utilizing a braiding protocol motivated by recent advances in electron-spin-resonance techniques we simulate quantum gates in 2D systems up to 600 sites, on timescales from a few femto- to nanoseconds. We demonstrate that the braiding process can be visualized in time and space by computing the non-equilibrium local density of states, which is proportional to the time-dependent differential conductance measured in scanning tunneling spectroscopy experiments, allowing us to directly image Majorana world lines.

Superconducting properties and materials↗
DOE OSTI2024

Absence of High-Pressure Ground-State Reentrant Ferroelectricity in PbTiO 3

We study ferroelectricity in the classic perovskite ferroelectric PbTiO 3 to high pressures with density functional theory (DFT) and experimental diamond-anvil techniques. We use second harmonic generation spectroscopy to detect lack of inversion symmetry. Consistent with early understanding and experiments, we find that ferroelectricity disappears at moderate pressures. However, DFT computations show that the disappearance arises from the overtaking of zone boundary instabilities, and not from the squeezing out of the off-centering ferroelectric displacements with pressure, as previously thought. Moreover, at high pressures the distorted perovskite phases are metastable with respect to a new dense centrosymmetric postperovskite phase with P⁢2 1 /m symmetry and 8-coordinated Ti, which becomes stable at about 70 GPa.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Understanding Defect Activation and Kinetics in Next Generation CdTe Absorbers

This project investigated the role of defects and dopants in cadmium telluride (CdTe) solar cells to improve efficiency and long-term stability. Advanced X-ray microscopy and spectroscopy techniques were used to map composition, identify defect structures, and measure charge collection at the nanoscale. These experimental results were combined with computational modeling to understand how dopants such as copper and arsenic interact with other elements during processing. The study found that many dopants become electrically inactive due to the formation of complexes with chlorine and oxygen, limiting carrier concentration and device performance. It also showed that selenium, used to enhance efficiency, can migrate within the material during both manufacturing and operation, altering local structure and potentially affecting stability. The project developed new diagnostic and analysis tools for studying photovoltaic materials and provided a mechanistic understanding of key performance limitations. These insights support the development of more efficient, stable, and cost-effective CdTe solar technologies for large-scale energy deployment.

14 SOLAR ENERGY↗
NASA NTRS1970

Applications of artificial intelligence for chemical inference. V.

Discussion of the modification of the DENDRAL computer program to extend the program to cyclic structures which exceed numerically the linear molecules of a given composition. IR, NMR and mass spectroscopy is used to develop a method for identification of each of the 27 possible ketones (exclusive of 5 cyclopropanones) of composition C6H10O.

Sheikh, Y. M.↗
NASA NTRS2003

Anharmonic Vibrational Spectroscopy of the F-(H20)n, complexes, n=1,2

We report anharmonic vibrational spectra (fundamentals, first overtones) for the F-(H(sub 2)O) and F-(H(sub 2)O)2 clusters computed at the MP2 and CCSD(T) levels of theory with basis sets of triple zeta quality. Anharmonic corrections were estimated via the correlation-corrected vibrational self-consistent field (CC-VSCF) method. The CC-VSCF anharmonic spectra obtained on the potential energy surfaces evaluated at the CCSD(T) level of theory are the first ones reported at a correlated level beyond MP2. We have found that the average basis set effect (TZP vs. aug-cc-pVTZ) is on the order of 30-40 cm(exp -1), whereas the effects of different levels of electron correlation [MP2 vs. CCSD(T)] are smaller, 20-30 cm(exp -1). However, the basis set effect is much larger in the case of the H-bonded O-H stretch of the F-(H(sub 2)O) cluster amounting to 100 cm(exp -1) for the fundamentals and 200 cm (exp -1) for the first overtones. Our calculations are in agreement with the limited available set of experimental data for the F-(H(sub 2)O) and F-(H(sub 2)O)2 systems and provide additional information that can guide further experimental studies.

Chaban, Galina M.↗
DOE OSTI2025

Revealing the evolution of order in materials microstructures using multi-modal computer vision

The development of high-performance materials for microelectronics, energy storage, and extreme environments depends on our ability to describe and direct property-defining microstructural order. Our present understanding is typically derived from laborious manual analysis of imaging and spectroscopy data, which is difficult to scale, challenging to reproduce, and lacks the ability to reveal latent associations needed for mechanistic models. Here, we demonstrate a multi-modal machine learning (ML) approach to describe order from electron microscopy analysis of the complex oxide La 1−x Sr x FeO 3 . We construct a hybrid pipeline based on fully and semi-supervised classification, allowing us to evaluate both the characteristics of each data modality and the value each modality adds to the ensemble. We observe distinct differences in the performance of uni- and multi-modal models, from which we draw general lessons in describing crystal order using computer vision.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Polariton spectra under the collective coupling regime. II. 2D non-linear spectra

In our previous work [Mondal et al., J. Chem. Phys. 162, 014114 (2025)], we developed several efficient computational approaches to simulate exciton–polariton dynamics described by the Holstein–Tavis–Cummings (HTC) Hamiltonian under the collective coupling regime. Here, we incorporated these strategies into the previously developed Lindblad-partially linearized density matrix (⁠$\mathscr{L}$-PLDM) approach for simulating 2D electronic spectroscopy (2DES) of exciton–polariton under the collective coupling regime. In particular, we apply the efficient quantum dynamics propagation scheme developed in Paper I to both the forward and the backward propagations in the PLDM and develop an efficient importance sampling scheme and graphics processing unit vectorization scheme that allow us to reduce the computational costs from $\mathscr{O}$($\mathscr{K}$ 2 )$\mathscr{O}$(T 3 ) to $\mathscr{O}$($\mathscr{K}$)$\mathscr{O}$(T 0 ) for the 2DES simulation, where $\mathscr{K}$ is the number of states and T is the number of time steps of propagation. As a result, we further simulated the 2DES for an HTC Hamiltonian under the collective coupling regime and analyzed the signal from both rephasing and non-rephasing contributions of the ground state bleaching, excited state emission, and stimulated emission pathways.

2D non-linear spectra↗
DOE OSTI2026

Attosecond response of molecules to impulsive ionization

When matter interacts with energetic radiation it can undergo sudden, or impulsive, ionization. This process can drive chemical change and occurs widely in space and planetary atmospheres, yet its comprehensive description challenges our current theoretical and computational capabilities as it requires advanced treatment of electron correlation and nonadiabatic dynamics beyond the Born–Oppenheimer approximation. Here, in this study, we measure the response of the para-aminophenol molecule to sudden ionization. Using attosecond X-ray absorption spectroscopy, we resolve the ultrafast dynamics of the ionized molecule with atomic precision. A subfemtosecond decay corresponds to states undergoing non-radiative decay, whereas few-femtosecond oscillatory signatures are associated with electronic wavepacket motion in stable cation states that later couple to nuclear motion. We compare our measurement with state-of-the-art computational modelling, qualitatively reproducing the observed response across multiple timescales. These results provide a benchmark for computational models of sudden ionization and ultrafast charge motion in matter.

Driver, Taran [SLAC National Accelerator Laborator↗
NASA NTRS2003

Research on Spectroscopy, Opacity, and Atmospheres

For planetary and telluric atmosphere projects the solar irradiance spectrum is required as the input at the top of the atmosphere. It has never been observed. People ask me to compute it. I can compute it theoretically using both known and predicted lines and get agreement averaged over a nanometer but there is no way to predict the resolved spectrum when only half the lines are known. In other stars the situation is worse because the signal-to-noise and resolution of the observations are worse. Logically one has to know a priori what is in the spectrum in order to interpret it; there is not enough information in the observed spectrum itself (qualifiers are given). Basically we need a list of all the energy levels of all atoms and molecules that matter. From that list can be generated all the lines. With the energy levels and line positions known, one can measure gf values, lifetimes, damping, or one can determine a theoretical or semiempirical Hamiltonian whose eigenvalues and eigenvectors produce a good match to the observed data, and that can then be used to generate additional radiative and collisional data for atoms or molecules.

Kurucz, Robert L.↗
NASA NTRS2004

Research on Spectroscopy, Opacity, and Atmospheres

I propose to continue providing observers with basic data for interpreting spectra from stars, novas, supernovas, clusters, and galaxies. These data will include allowed forbidden line lists both laboratory and computed, for the first five to ten ions of all atoms and for all relevant diatomic molecules. I will eventually expend to all ions of the first thirty elements to treat far UV end X-ray spectra, and for envelope opacities. I also include triatomic molecules providing by other researchers. I have made CDs with Partridge and Schwanke's water data for work on M stars.The luna data also serve as input to my model atmosphere and synthesis programs that generated energy distributions, photometry, limb darkening, and spectra that can be used for planning observations and for fitting observed spectra. The spectrum synthesis programs produce detailed plots with the line identified. Grids of stellar spectra can be used for radial velocity-, rotation-, or abundance templates and for population synthesis. I am fitting spectra of bright stars to test the data and to produce atlases to guide observer. For each star the whole spectrum is computed from the UV to the far IR. The line data, opacities, models, spectra, and programs are freely distributed on CDs and on my web site and represent a unique resource for many NASA programs.

Oliversen, Ronald↗
NASA NTRS1995

Cooperative Testing of Rocket Injectors That Use Gaseous Oxygen and Hydrogen

Gaseous oxygen and hydrogen propellants used in a special engine energy cycle called Full-Flow Staged Combustion are believed to significantly increase the lifetime of a rocket engine's pumps. The cycle can also reduce the operating temperatures of the engine. Improving the lifetime of the hardware reduces its overall maintenance and operations costs, and is critical to reducing costs for the joint NASA/industry Reusable Launch Vehicle (RLV). The work in this project will demonstrate the performance and lifetime of one-element and many-element combustors with gaseous O2/H2 injectors. This work supporting the RLV program is a cooperative venture of the NASA Lewis Research Center, the NASA Marshall Space Flight Center, Rocketdyne, and the Pennsylvania State University. Information about gas-gas rocket injector performance with O2/H2 is very limited. Because of this paucity of data, new testing is needed to improve the knowledge base for testing and designing new injectors for the RLV and to improve computer models that predict the combusting gas flows of new injector designs. Therefore, detailed observations and measurements of the combusting flow from many-element injectors in a rocket engine are being sought. These observations and measurements will be done with three different tools: schlieren photography, ultraviolet imaging, and Raman spectroscopy. The schlieren system will take photos of the density differences in combusting flow, the ultraviolet movies will determine the location of the hydroxyl (OH) radical in the combustion flow, and the Raman spectroscopic measurements will provide the combustion temperature and amount of water (H2O), hydrogen (H2), and oxygen (O2) in the combustor. Marshall is providing overall program management, design and computational fluid dynamics (CFD) analyses, as well as funding for the work at Penn State. An existing, windowed combustor and several injectors will be provided by Rocketdyne--two injectors for the initial screening tests and one with an optimized design based on the best design found in the screening tests. Lewis will provide a nozzle and several injectors for the screening test program. The configuration of the injectors will be based on a design chosen by all the participants, and their elements will be based on the coaxial and impinging flow. Lewis also will provide the instrumentation for the flow-field measurements: schlieren, ultraviolet imaging, and Raman spectroscopy. In addition, thermocouples will measure heat flow on the injector face. Other traditional measurements of rocket performance will be made as well: chamber pressure, mass flow of each propellant, purge flow, and the barrier cooling gas flow. Penn State will conduct single-element testing with the injector elements from both the Rocketdyne and the jointly designed injectors. A wide variety of traditional and nontraditional injector designs will be tested in this program. The results will be valuable in computational fluid dynamics code validation and overall rocket combustion efficiency measurements. Correlations between combustion efficiency, laser measurements of species, and ultraviolet and visible light photography will also be made. Thus far, several different single-element injectors have been tested at Penn State and Lewis. The experimental setup of a rocket engine with a viewing window is shown. The combusting flow is shown. The results are helping engineers design the many element injectors.

Source record↗
DOE OSTI2025

Computational toolkit for predicting thickness of 2D materials using machine learning and autogenerated dataset by large language model

The thickness of 2D materials not only plays a crucial role in determining the performance of nanoelectronic and optoelectronic devices but also introduces complexities in predicting volume-dependent properties, such as energy storage capacity, due to the intrinsic vacuum within these materials. Although a plethora of experimental techniques, including but not limited to optical contrast, Raman spectroscopy, nonlinear optical spectroscopy, near-field optical imaging, and hyperspectral imaging, facilitate the measurement of 2D material thickness, comprehensive data for many materials remain elusive. Over the past decade, the exponential proliferation of 2D materials and their heterostructures has outstripped the capabilities of conventional experimental and computational approaches. In this evolving landscape, machine learning (ML) has emerged as an indispensable tool, offering a scalable approach to augment these traditional methodologies. Addressing the critical gap, we introduce THICK2D—Thickness Hierarchy Inference and Calculation Kit for 2D Materials. This Python-based computational framework harnesses an autogenerated thickness database, developed using large language models, and advanced ML algorithms to facilitate the rapid and scalable estimation of material thickness, relying solely on crystallographic data. To demonstrate the utility and robustness of THICK2D, we successfully used the toolkit to predict the thickness of more than 8000 2D-based materials, sourced from two extensive 2D materials databases. THICK2D is disseminated as an open-source utility, accessible on GitHub at https://github.com/gmp007/THICK2D, and archived on Zenodo at https://10.5281/zenodo.11216648.

Ekuma, Chinedu E. (ORCID:0000000258527556)↗
DOE OSTI2024

A Bottom-Up Approach to Rational Design of Crystalline Materials: Investigation of Vibronic Coherences Underlying Exciton Dynamics in Semiconductors

In this project we uncovered structure-function relationships of donor-acceptor co-crystals used to develop next-generation optoelectronic devices. Unraveling the photodynamics of molecular crystalline materials poses many challenges for spectroscopy due to broad, overlapping features representing numerous underlying dynamical processes. This leads researchers to make many assumptions about the dynamics of a system in choosing an appropriate kinetic fitting model. Computationally, electronic structure methods are either prohibitively expensive or underdeveloped for computing the excited state structure of molecular materials, especially states that exhibit charge transfer. Researchers must therefore perform calculations of excited electronic states using truncated models of molecular materials. Here we present a joint experimental-theoretical approach to bridging the gap between the photodynamics of a molecular material and its constituent molecules. We focus our efforts on quantifying the timescales and mechanisms of photoexcitation in donor-acceptor co-crystals and donor-acceptor dimers where the lowest-lying excited state is characterized by charge transfer from the donor to the acceptor. We employ ultrafast UV pump, UV-Vis probe transient absorption spectroscopy to unravel the time-resolved spectroscopic signatures of the photodynamics in both the crystalline material and donor-acceptor dimers in solution. We perform electronic structure and excited state dynamics calculations of the dimers to inform kinetic fitting models and assign the spectral features. The photodynamics of the crystal vs. dimer systems have many similarities, enabling unprecedented insights into the formation and evolution of charge transfer excitons in the crystalline systems.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Using Neural Networks to Identify Mixture Components in Hyperspectral Reflectance Data

Neural networks have been employed to identify materials of interest from hyperspectral data (generally imagery) based on their unique spectral signatures. This approach assumes that there is a single material that is standing out from the rest of the spectrum to be identified. However, pixels often contain more than one material, or a material of interest may itself be a mixture of multiple materials. Neural networks are only as good as the data used to train them, and it takes a great deal of work in the laboratory to identify, make, and measure all potential mixtures of interest. Thus, researchers often calculate synthetic spectra using algorithms with varying degrees of fidelity to the physics that govern the interactions between light and multiple materials. In this work, we have (1) adapted a neural network designed to identify mixture components from Raman spectroscopy to work with visible to near‐infrared reflectance data and (2) tested three common mixture algorithms to determine the most accurate and least computationally expensive method to build synthetic training datasets. With our initial test dataset, we have achieved accuracies of > 90% and found that the synthetic training dataset produced using the Hapke mixture model provides the best results.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Charge Transfer and Recombination Pathways through Fullerene Guests in Porphyrin-Based MOFs

Porphyrin-based metal–organic frameworks (MOFs) offer a unique platform for building porous donor–acceptor networks that exhibit long-lived charge separation and transport upon incorporation of electron acceptor guest species. Here, in this work, porphyrin-based MOFs, PCN-222(H 2 ) and PCN-222(Zn), synthesized as nanoparticle suspensions, are successfully infiltrated with fullerene acceptor molecules, C 60 or PC 61 BM, in both polar and nonpolar solvent environments. The location and relative binding strength of these guest species are evaluated through a combination of N 2 physisorption measurements, photoluminescence quenching, and UV–vis absorption titration experiments. Semiempirical tight binding calculations are used to screen potential locations of the fullerene guest within the MOF pores, and hybrid density functional theory (DFT)-computed interaction energies confirm the energetically favorable positions. The fundamental photophysics of these donor–acceptor host–guest combinations are probed using ultrafast transient absorption spectroscopy. Sub-picosecond electron transfer involving initial exciplex population is observed, with slow charge recombination lifetimes on the order of τ ~1 ns for all systems in both dimethylformamide and 1,4-dioxane. Charge recombination occurs through population of fullerene and/or framework porphyrin triplet states depending on the porphyrin metalation status. The photophysics of the fullerene-loaded MOFs are discussed in the context of relevant porphyrin–fullerene donor–acceptor molecules to highlight the unique role of the framework environment in dictating photoinduced electron transfer and decay pathways.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗