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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Mitigating coherent loss in superconducting circuits using molecular self-assembled monolayers

In planar superconducting circuits, decoherence due to materials imperfections, especially two-level-system (TLS) defects at different interfaces, is a primary hurdle for advancing quantum computing and sensing applications. Traditional methods for mitigating TLS loss, such as etching oxide layers at metal and substrate interfaces, have proven to be inadequate due to the persistent challenge of oxide regrowth. In this work, we introduce a novel approach that employs molecular self-assembled monolayers (SAMs) to chemically bind at different interfaces of superconducting circuits. This technique is specifically tested here on coplanar waveguide (CPW) resonators, in which this method not only impedes oxide regrowth after surface etching but can also tailors the dielectric properties at different resonators interfaces. The deployment of SAMs results in a consistent improvement in the measured quality factors across multiple resonators, surpassing those with only oxide-etched resonators. The efficiency of our approach is supported by microwave measurements of multiple devices conducted at millikelvin temperatures and correlated with detailed X-ray photoelectron spectroscopy (XPS) and transmission electron microscopy (TEM) characterizations of SAM-passivated resonators. The compatibility of SAMs materials with the established fabrication techniques offers a promising route to improve the performance of superconducting quantum devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2021

Multi-Angle Imager for Aerosols (MAIA) spectral and radiometric calibration

The Multi-angle Imaging SpectroRadiometer (MISR) was launched as part of NASA’s Terra satellite suite of instruments. Still operational, it makes use of observations from multiple view angles to retrieve aerosol abundance and particle properties. The Multi-Angle Imager for Aerosols (MAIA) instrument improves on this heritage by incorporating polarimetry and an expanded spectral range. Combining these data with surface measurements, the relationship between pollution and human health will be explored. MAIA has just completed camera testing, building on the experience from MISR. Spectral calibration now makes use of a double subtractive monochromator, built with the intent to allow the exit slit output to be uniform in spectral content. For radiometric testing, hardware upgrades have included adding UV lamps to the 1.65 cm (65") integrating sphere, use of a NIST-traceable sphere to establish absolute radiances, and the addition of a UV transfer spectrometer to support characterization of the sphere output from 300 to 2500 nm. During camera build, Newton’s rings were observed in the detector Quantum Efficiency (QE) measurements. This is due to etaloning within the detector itself. Etaloning was also evident in the spectral and radiometric characterizations performed on the completed camera. Spectral metrics, including center wavelength and width, are presented here using a moment’s analysis. This better represents the band properties, particularly in bands where fringing is observed, as compared to a full-width at half-maximum determination. It is believed that the MAIA camera has been carefully characterized, and meet its spectral and radiometric requirements.

Harten, Gerard Van↗
NASA NTRS1979

Shallow-homojunction GaAs solar cells

Single-crystal GaAs shallow-homojunction solar cells on GaAs or Ge substrates, without Ga sub 1-x Al sub x As window layers, that have conversion efficiencies exceeding 20% at AM1 (17% at AMO). Using a simple theoretical model, good fits were obtained between computer calculations and experimental data for external quantum efficiency and conversion efficiency of cells with different values of n+ layer thickness. The calculations not only yield values for material properties of the GaAs layers composing the cells but will also permit the optimization of cell designs for space and terrestrial applications. Preliminary measurements indicate that the shallow-homojunction cells are resistant to electron irradiation. In the best test so far, bombardment with 1 x 10 to the 16th power/sq cm fluence of 1 MeV electrons reduced the short-circuit current by only about 6%.

Fan, J. C. C.↗
DOE OSTI2025

Leveraging Natural Language Processing and Generative Models in Molecular Chemistry: Property Prediction and Novel Compound Generation

The accurate prediction of molecular properties is important for the rational design and the advancement of green chemistry and sustainable materials research. However, the predictive power of traditional computational chemistry methods is limited due to computational restrictions. Here, in this study, we examine an alternative approach to the accurate prediction of properties of organic compounds: natural language processing (NLP)-based molecular embedding. Using viscosity, partition coefficient (log P), and enthalpy of vaporization as test properties through a survey of comprehensive datasets comprising 5695 data points for viscosity, 25 870 data points for log P, and 2296 data points for enthalpy of vaporization. These are important properties for the design of greener, safer, and sustainable chemical processes. Models were trained using NLP methods such as Mol2vec and fine-tuned ChemBERTa, and results were compared with traditional input featurization techniques such as Morgan fingerprints and quantum chemistry derived sigma profiles and DFT features. Among the various machine learning models, Mol2vec demonstrated superior predictive capabilities, achieving the highest correlation coefficient (R 2 = 0.945) and lowest RMSE (0.106 mPa s) for viscosity, as well as high accuracy for log P and enthalpy of vaporization predictions. These findings establish the Mol2vec featurization technique, graph-convolutional neural networks (GCNN), and fine-tuned ChemBERTa model as powerful tools for predictive modeling of organic compounds properties, offering a significant improvement over previously used featurization techniques and opening up strategies for very-high-throughput computational screening. Finally, we integrated ML models with hybrid language-model-based generative adversarial networks (LM-GAN) to generate novel molecular sequences with desirable properties for different research applications. The ability to computationally design solvents with lower viscosity, lower log P, and lower enthalpy of vaporization offers a data-driven route to accelerating the discovery of sustainable alternatives to traditionally toxic solvents.

ChemBERTa↗
DOE OSTI2024

Quantum tensor network algorithms for evaluation of spectral functions on quantum computers

We investigate quantum algorithms derived from tensor networks to simulate the static and dynamic properties of quantum many-body systems. Using a sequentially prepared quantum circuit representation of a matrix product state (MPS) that we call a quantum tensor network (QTN), we demonstrate algorithms to prepare ground and excited states on a quantum computer and apply them to molecular nanomagnets (MNMs) as a paradigmatic example. In this setting, we develop two approaches for extracting the spectral correlation functions measured in neutron-scattering experiments: (a) a generalization of the SWAP test for computing wave function overlaps and, (b) a generalization of the notion of matrix product operators to the QTN setting which generates a linear combination of unitaries. The latter method is discussed in detail for translationally invariant spin-half systems, where it is shown to reduce the qubit resource requirements compared with the SWAP method and may be generalized to other systems. We demonstrate the versatility of our approaches by simulating spin-1/2 and spin-3/2 MNMs, with the latter being an experimentally relevant model of a Cr$^{3+}_{8}$ ring. Here, our approach has qubit requirements that are independent of the number of constituents of the many-body system and scale only logarithmically with the bond dimension of the MPS representation, making them appealing for implementation on near-term quantum hardware with mid-circuit measurement and reset.

Neutron scattering↗
DOE OSTI2026

Benchmarking quantum trial wavefunctions for phaseless auxiliary-field quantum Monte Carlo

The phaseless auxiliary-field quantum Monte Carlo (ph-AFQMC) method is a stochastic imaginary-time projection technique for computing ground-state properties of strongly correlated quantum systems, with accuracy that depends critically on the choice of trial wavefunction. Here, we investigate ph-AFQMC with trial states prepared using parameterized quantum circuits. In this work, we present a comprehensive benchmarking study of quantum trial wavefunctions spanning unitary coupled-cluster, Hamiltonian-informed, Jastrow-inspired, and adaptively constructed ansatze. The benchmarking evaluates accuracy, expressibility, and scalability of these ansatze within the QC-AFQMC framework. We test these ansatze on linear hydrogen chains under bond stretching and find that several ansatz families produce chemically accurate ph-AFQMC energies across the dissociation curve. We have performed simulations using the CUDA-Q quantum development platform on the GPU partition of the Perlmutter supercomputer. When comparing ansatze at similar numbers of variational parameters, we find that different ansatz families yield comparable ph-AFQMC results despite exhibiting substantially different variational energies, optimization costs, and circuit depths. Our results indicate that the variational energy of an ansatz is not always a reliable indicator of its quality for ph-AFQMC and reveal instances of over-parameterization. In the strongly correlated regime, trial wavefunctions obtained from adaptive ansatze, exemplified here by ADAPT-VQE with the UCCSD operator pool, can outperform their fixed-ansatz counterparts (UCCSD) in terms of projected energies while using substantially more compact circuits, providing a flexible route to optimize quantum resources within the ph-AFQMC framework.

Rofougaran, Rod [LBNL, Berkeley; Columbia U.; PNL,↗
DOE OSTI2025

Development Of Non-Invasive Beam Diagnostics By Quantum Optics-Based Detection

We report our effort and latest progress developing diagnostics using quantum optics-based detection method for determining the spatial properties and current of electron beams. As electrons pass through a dilute vapor of rubidium atoms, their magnetic field perturb the atomic spin’s quantum state and causes polarization rotation of a laser resonant with an optical transition of the atoms. By measuring the polarization rotation angle across the laser beam, we recreate a 2D projection of the magnetic field and use it to determine the e-beam position, size and total current. We tested this method for an e-beam with currents ranging from 30 to 110 µA. Our study shows this approach is insensitive to electron kinetic energy, and is initially verified experimentally between 10 to 20 keV. A different approach was also performed with highly excited rubidium atoms in Rydberg states through a coherent two photon process. We use this detection scheme to measure the electric field generated by a

Zhang, S. [Thomas Jefferson National Accelerator F↗
NASA NTRS1985

Identification and properties of molecular systems of potential use in solar-pumped lasers

The concepts and computational tools of theortical chemistry are used to investigate molecular properties needed in direct solar-pumped lasers. Compounds of the type RR'CXY, with R and R' organic groups, and X and Y halide atoms were identified as likely candidates because of their highly enhanced absorption coefficients over compounds with a single halide atom. The use of a combination of vibrational excitation followed by electronic excitation to enhance quantum yields at certain wavelengths is indicated. A self-consistent eikonal approximation to state-to-state transitions was tested for CH3I and is useful for other problems involving electronic energy and charge transfer. An approach to calculate potential energy surfaces and transition dipoles was developed which is based on the generation of eigenstates of the nonrelativisitc Hamiltonian followed by incorporation of the spin-orbit coupling by configuration interaction.

Micha, D. A.↗
DOE OSTI2025

Tunable and Robust Optical and Structural Properties of a Cooperative Squaraine-Dye Aggregate-DNA DX-DAE Tile System

Molecular excitons, which are excitations delocalized over multiple dyes in a wavelike manner, are of interest for a wide range of applications, including quantum information science. Numerous studies have templated a variety of synthetic dyes via a DNA scaffold to induce dye aggregation to create molecular excitons upon photoexcitation. Dye aggregate optical properties are critically dependent on relative dye geometry and local environment; therefore, an understanding of dye-dye and DNA-dye interactions is critical for advancing toward more complex DNA-dye systems. The extensively studied DNA Holliday junction (HJ) and less-studied double-crossover (DX) tile motif are fundamental test beds for designing complex and ultimately modular DNA-dye architectures. Here, we report the first study of single-linked squaraine dye aggregation and exciton delocalization on a larger and more stable (compared with the HJ) DX tile motif. We first highlight a few DNA-dye constructs that support single dyes and aggregates with distinct optical properties that are both tunable—through sample design, buffer conditions, and heat treatment—and robust to environment changes, including transfer to solid phase. Next, we assess several experimental and design considerations that demonstrate directed dye-driven assembly of a novel double-tile DNA configuration. Our results demonstrate that single-linked squaraine dyes templated to DX tiles provide a viable research path to design and evaluate dye aggregate networks that support exciton delocalization. We include herein the first report of exciton delocalization in the solid phase in a DNA-dye construct. Additionally, our findings indicate that dye aggregation impacts the assembly of the DNA-dye construct, and, in some cases, thereby cooperates with the DNA to determine a final robust system configuration. Finally, we show that a controlled annealing schedule can be employed to promote the homogeneous assembly of DNA-dye constructs. The findings in this study contribute to the understanding of DNA-dye systems and the relevant factors involved in their directed assembly to achieve specific constructs with desirable properties.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Quantum chromodynamics resolution of the ATOMKI anomaly in 4 He nuclear transitions

Observations of anomalous angular correlations in electron-positron pairs produced from excited states of 4 He, 8 Be, and 12 C nuclei have been suggested as being due to the creation and subsequent decay of a new light particle of mass ~17MeV. In this work, we investigate the possibility that the source of the observed signals is a set of new excitation channels created by the 12-quark hidden-color Fock state within the 4 He nuclear wave function dubbed the “hexadiquark.” We calculate the invariant e + ⁢ e - mass spectrum for the electromagnetic transition from a new excitation of 4 He, estimating its differential and total decay width. We find that we can fit the shape of the anomalous signal with the QCD Fock state at excitation energy E* = 17.9 ± 1MeV and a Gaussian form factor for the electromagnetic decay. We address the physical issues with the fit parameters using properties of the hexadiquark state, in particular the three weakly repulsive 6 C interactions of SU⁡(3) C between diquark pairs. Experimental tests of our model are described in detail. In light of this work, we emphasize the need for independent experimental confirmation or refutation of the ATOMKI results as well as dedicated experiments to search for the proposed new excitations of 4 He and other a-cluster nuclei.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2004

Analysis of Electrical Characteristics of Thin Film Photovoltaic Cells

Solar energy is the most abundant form of energy in many terrestrial and extraterrestrial environments. Often in extraterrestrial environments sunlight is the only readily available form of energy. Thus the ability to efficiently harness solar energy is one of the ultimate goals in the design of space power systems. The essential component that converts solar energy into electrical energy in a solar energy based power system is the photovoltaic cell. Traditionally, photovoltaic cells are based on a single crystal silicon absorber. While silicon is a well understood technology and yields high efficiency, there are inherent disadvantages to using single crystal materials. The requirements of weight, large planar surfaces, and high manufacturing costs make large silicon cells prohibitively expensive for use in certain applications. Because of silicon s disadvantages, there is considerable ongoing research into alternative photovoltaic technologies. In particular, thin film photovoltaic technologies exhibit a promising future in space power systems. While they are less mature than silicon, the better radiation hardness, reduced weight, ease of manufacturing, low material cost, and the ability to use virtually any exposed surface as a substrate makes thin film technologies very attractive for space applications. The research group lead by Dr. Hepp has spent several years researching copper indium disulfide as an absorber material for use in thin film photovoltaic cells. While the group has succeeded in developing a single source precursor for CuInS2 as well as a unique method of aerosol assisted chemical vapor deposition, the resulting cells have not achieved adequate efficiencies. While efficiencies of 11 % have been demonstrated with CuInS2 based cells, the cells produced by this group have shown efficiencies of approximately 1 %. Thus, current research efforts are turning towards the analysis of the individual layers of these cells, as well as the junctions between them, to determine the cause of the poor yields. As a student of electrical engineering with some material science background, my role in this research is to develop techniques for analyzing the electrical characteristics of the CuInS2 cells. My first task was to design a shadow mask to be used to place molybdenum contacts under a layer of CuInS;! in order to analyze the contact resistance between the materials. In addition, I have also analyzed evaporated aluminum top contacts and have tested various methods of increasing their thicknesses in order to decrease series resistance. More recently I have worked with other members of the research group in reviving a vertical cold-wall reactor for experimentation with CuInS2 quantum dots. As part of that project, I have improved the design for a variable frequency and pulse width square wave generator to be used in driving the precursor injection process. My task throughout the remainder of my tenure is to continue to analyze and develop tools for the analysis of electrical properties of the CuInS2 cells with the ultimate goal of discovering ways to improve the efficiency of our photovoltaic cells. Traditionally, photovoltaic cells are based on a single crystal silicon absorber. While The research group lead by Dr. Hepp has spent several years researching copper indium

Kasick, Michael P.↗
DOE OSTI2026

Bio-Inspired Energy-Efficient Nanofabricated Electrical Contacts

Nanoscale electrical contacts, especially those between materials of dissimilar electronic properties, often represent one of the main causes of drops in energy transfer efficiency. They are also among the sources of above-threshold noise, and their performance often decreases over the lifetime of the nanodevices. Scale-down limitations from mesoscopic to nanoscale devices, and likewise, of nanoscale to quantum-scale devices are also impeded by contacts’ quality. Making more reliable, energy-efficient electrical contacts is among the goals of the nanoelectronics research within the framework of energy-efficient electronic systems. This report focuses on the design, nanofabrication, and testing of novel shapes of electrical contacts. Lithography and nanofabrication were utilized to mimic the approximate shape of insect setae for mesoscale contacts design. The contacts are tested for elementary charge transport via I–V curves and for the broadband, 1/f noise. Tests show that contacts design leads to a measurable decrease in the energy necessary to operate a contact as a switch by at least 12–20%, depending on temperature, while broadband noise shows measurably lower power spectra, for bio-inspired contacts. The proposed method is open to modifications and improvements as required by various on-chip applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Upstreamness and downstreamness in input–output analysis from local and aggregate information

Abstract Ranking sectors and countries within global value chains is of paramount importance to estimate risks and forecast growth in large economies. However, this task is often non-trivial due to the lack of complete and accurate information on the flows of money and goods between sectors and countries, which are encoded in input–output (I–O) tables. In this work, we show that an accurate estimation of the role played by sectors and countries in supply chain networks can be achieved without full knowledge of the I–O tables, but only relying on local and aggregate information, e.g., the total intermediate demand per sector. Our method, based on a rank-1 approximation to the I–O table, shows consistently good performance in reconstructing rankings (i.e., upstreamness and downstreamness measures for countries and sectors) when tested on empirical data from the world input–output database. Moreover, we connect the accuracy of our approximate framework with the spectral properties of the I–O tables, which ordinarily exhibit relatively large spectral gaps. Our approach provides a fast and analytically tractable framework to rank constituents of a complex economy without the need of matrix inversions and the knowledge of finer intersectorial details.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Enhancing the efficiency of time-dependent density functional theory calculations of dynamic response properties

X-ray Thomson scattering (XRTS) constitutes an essential technique for diagnosing material properties under extreme conditions, such as high pressures and intense laser heating. Time-dependent density functional theory (TDDFT) is one of the most accurate available ab initio methods for modeling XRTS spectra, as well as a host of other dynamic material properties. However, strong thermal excitations, along with the need to account for variations in temperature and density as well as the finite size of the detector significantly increase the computational cost of TDDFT simulations compared to ambient conditions. In this work, we present a broadly applicable method for optimizing and enhancing the efficiency of TDDFT calculations. Our approach is based on a one-to-one mapping between the dynamic structure factor and the imaginary time density–density correlation function, which naturally emerges in Feynman’s path integral formulation of quantum many-body theory. Specifically, we combine rigorous convergence tests in the imaginary time domain with a constraints-based attenuation of narrow-band fluctuations to improve the efficiency of TDDFT modeling without the introduction of any significant bias. As a result, we can report a speed-up by up to an order of magnitude, thus substantially reducing the burden of computational cost required for XRTS analysis.

Moldabekov, Zhandos A. [Helmholtz-Zentrum Dresden-↗
NASA NTRSDate not supplied

Predicting Melt Properties Using Atomistic Simulations With A Highly Accurate Physically Informed Neural Network Interatomic Potential

The use of a recently developed machine learning (ML) interatomic potential for molecular dynamics simulations of aluminum melt properties will be presented. Such properties are critical for process modeling in additive manufacturing, including the melt pool size, solidification, and formation of solidification microstructures. Direct first-principles modeling of these processes is computationally prohibitive whereas simulations employing ML potentials combine the high accuracy of quantum-mechanical methods with high computational speeds. The physically-informed neural network (PINN) method used herein, integrates a high-dimensional regression implemented by an artificial neural network with a physics-based bond-order interatomic potential. PINN potentials can accurately reproduce many properties of aluminum in both crystalline-solid and liquid phases. We examine the accuracy of a PINN Al potential in predicting the density, self-diffusivity, viscosity, and the tension of the liquid surface and liquid-solid interfaces. Comparison with experimental data and ab initio molecular dynamics calculations shows very good agreement for all properties tested.

molecular dynamics↗
DOE OSTI2025

QCD moat regime and its real-time properties

Dense quantum chromodynamics (QCD) matter may exhibit crystalline phases. Their existence is reflected in a moat regime, where mesonic correlations feature spatial modulations. We study the real-time properties of pions at finite temperature and density in QCD in order to elucidate the nature of this regime. We show that the moat regime arises from particle-hole-like fluctuations near the Fermi surface. This gives rise to a characteristic peak in the spectral function of the pion at nonzero spacelike momentum. This peak can be interpreted as a new quasi particle, the moaton. In addition, our framework also allows us to directly test the stability of the homogeneous chiral phase against the formation of an inhomogeneous condensate in QCD. We find that an inhomogeneous instability is highly unlikely for baryon chemical potentials μ B ≤ 630 MeV . Published by the American Physical Society 2025

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Dynamic, symmetry-preserving, and hardware-adaptable circuits for quantum computing many-body states and correlators of the Anderson impurity model

We present a hardware-reconfigurable ansatz on N q -qubits for the variational preparation of many-body states of the Anderson impurity model (AIM) with N imp + N bath = N q /2 sites, which conserves total charge and spin z component within each variational search subspace. The many-body ground state of the AIM is determined as the minimum over all minima of O(N$^2_ q$) distinct charge-spin sectors. Hamiltonian expectation values are shown to require ω(N q ) < N meas. $\leqslant$ O(N imp N bath ) symmetry-preserving, parallelizable measurement circuits, each amenable to postselection. To obtain the one-particle impurity Green’s function we show how initial Krylov vectors can be computed via midcircuit measurement and how Lanczos iterations can be computed using the symmetry-preserving ansatz. For a single-impurity Anderson model with a number of bath sites increasing from one to seven, we show using numerical emulation that the ease of variational ground-state preparation is suggestive of linear scaling in circuit depth and subquartic scaling in optimizer complexity. We therefore expect that, combined with time-dependent methods for Green’s function computation, our ansatz provides a useful tool to account for electronic correlations on early fault-tolerant processors. Finally, with a view towards computing real materials properties of interest like magnetic susceptibilities and electron-hole propagators, we provide a straightforward method to compute many-body, time-dependent correlation functions using a combination of time evolution, midcircuit measurement-conditioned operations, and the Hadamard test.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Hydrothermal Growth of Magnetically Frustrated Crystals: Lanthanide Stannate Pyrochlores as a Prototype

One important test bed system for frustrated magnetism is the pyrochlore lattice with the formula A2B2O7 in the cubic space group Fd3(-)m. Both the A and B sites occupy crystallographic trigonal sites and both sites possess a tetrahedral relationship with the other similar metal ion sites. These symmetry relationships generate a 3 D frustrated structure. In frustrated magnetic systems, typically a trivalent lanthanide ion occupies the A site and a magnetically silent tetravalent ion (Ti, Zr, Sn, etc.) occupies the B site. A classical problem related to the crystal growth of these compounds is sample quality. As refractory oxides, the traditional synthesis and crystal growth techniques require high temperatures, which creates two problems that are quite common and endemic to the pyrochlores. One is oxide lattice defects and the other is A/B site disorder. Both issues often occur in the same crystals at the same time and can have a significant impact on the study of physical properties. A hydrothermal approach can be applied to this problem. The relatively low crystal growth temperatures (600-720˚C) greatly minimize nonstoichiometry, lattice defects and A/B site disorder. The reduction of these pervasive imperfections significantly increases the quality of the observed physical property data. This talk will focus on the lanthanide stannates Ln2Sn2O7 as a prototype test bed of these systems. The stannates are among the few building blocks that can stabilize the pyrochlore structure type for all the lanthanides and they serve as an excellent proving ground for a wide range of physical properties. The synthesis and crystal growth of the lanthanide stannates will be reviewed, along with a discussion of some of the physical properties that result from the frustrated magnetic states of these low defect crystals.

Hydrothermal, crystal growth↗