SEARCH · Engineering Papers

Results for “Complexity theory”

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.

SourceResearch connectionFrom yearThrough year

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

At least 1,495 records · Page 83

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Modeling the Behavior of Complex Aqueous Electrolytes Using Machine Learning Interatomic Potentials: The Case of Sodium Sulfate

Understanding the structure and thermodynamics of solvated ions is essential for advancing applications in electrochemistry, water treatment, and energy storage. While ab initio molecular dynamics methods are highly accurate, they are limited by short accessible time and length scales whereas classical force fields struggle with accuracy. Herein, we explore the structure and thermodynamics of complex monovalent-divalent ion pairs using Na 2 SO 4 (aq) as a case study by applying a machine learning interatomic potential (MLIP) trained on density functional theory (DFT) data. Our MLIP-based approach reproduces key bulk properties such as density and radial distribution functions of water. We provide the hydration structure of the sodium and sulfate ions in the 0.1–2 M concentration range and the one-dimensional and two-dimensional potentials of mean force for the sodium–sulfate ion pairing at the low concentration limit (0.1 M), which are inaccessible to DFT. At low concentrations, the sulfate ion is strongly solvated, leading to the stabilization of solvent-separated ion pairs over contact ion pairs. Minimum energy pathway analysis revealed that coordinating two sodium ions with a sulfate ion is a multistep process whereby the sodium ions coordinate to the sulfate ion sequentially. Finally, we demonstrate that MLIPs allow the study of solvated ions beyond simple monovalent pairs with DFT-level accuracy in their low concentration limit (0.1 M) via statistically converged properties from ns-long simulations.

anions↗

DOE OSTI2025

Computational Analysis of the Energetic Stability of High-Entropy Structures of a Prototypical Lanthanide-Based Metal–Organic Framework

High-entropy materials are characterized by their complex compositions, typically comprising five or more elements in near-equiatomic proportions. Applying this concept to metal ions in metal−organic frameworks (MOFs) has paved the way for exploring a new class of high-entropy MOFs. While the compositional strategy of high-entropy materials leverages configurational entropy to aid thermodynamic stability, it also poses significant analytical challenges due to the vast compositional landscape and diverse phases that these materials can adopt. We present a computational study of several complexities associated with selecting potential high-entropy versions of a prototype lanthanidebased MOF. We compute the energetics of metal mixing of these heterometallic MOFs using density functional theory (DFT) and machine learning interatomic potential (MLIP) methods. The use of MLIP methods allows a systematic exploration of the convex hull of thermodynamically stable MOF structures containing up to 5 distinct metals.

Chemical structure↗

DOE OSTI2021

Self-Assembly of Flexible Linear–Semiflexible Bottlebrush–Flexible Linear Triblock Copolymers

Block copolymer (BCP) self-assembly is a fundamental process in which incompatible blocks spontaneously form organized microstructures with broad practical applications. Classical understanding is that the domain spacing is limited by the contour length of the polymer backbone. Here, using a combination of molecular design, chemical synthesis, small-/wide-angle X-ray scattering, transmission electron microscopy, and electron tomography, we discover that this molecular picture does not hold for architecturally semiflexible BCPs. For strongly segregated linear–semiflexible bottlebrush–linear triblock copolymers, the size of the bottlebrush domain can be twice the bottlebrush backbone contour length. The mechanism of such anomalous self-assembly is likely that the interfacial repulsion between the incompatible blocks is large enough to pull a part of the linear end blocks into the bottlebrush domain. This effectively increases the bottlebrush domain size. Moreover, the semiflexible bottlebrush widens the regime for the cylinder morphology that is associated with the volume fraction of the end blocks fC SFB ∈ (0.10, >0.41). This window is much wider than that for flexible linear BCPs, fC F ∈ (0.14, 0.35), and that predicted by the recent self-consistent field theory for linear-bottlebrush BCPs of the same chemistry and molecular architecture. Finally, our experimental findings reveal previously unrecognized mechanisms for the self-assembly of architecturally complex BCPs.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Spin dynamics in the skyrmion-host lacunar spinel GaV 4 S 8

Here in the lacunar spinel GaV 4 S 8 , the interplay of spin, charge, and orbital degrees of freedom produces a rich phase diagram that includes an unusual Néel-type skyrmion phase composed of molecular spins. To provide insight into the interactions underlying this complex phase diagram, we study the spin excitations in GaV 4 S 8 through inelastic neutron scattering measurements on polycrystalline and single crystal samples. Using linear spin wave theory, we describe the spin wave excitations using a model where V 4 clusters decorate an fcc lattice. The effective cluster model includes a ferromagnetic interaction and a weaker antisymmetric Dzyaloshinskii-Moriya interaction between the neighboring molecular spins. Our work clarifies the spin interactions in GaV 4 S 8 and supports the picture of interacting molecular clusters.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

Self-supervised physics-informed generative networks for phase retrieval from a single X-ray hologram

X-ray phase contrast imaging significantly improves the visualization of structures with weak or uniform absorption, broadening its applications across a wide range of scientific disciplines. Propagation-based phase contrast is particularly suitable for time- or dose-critical in vivo/in situ/operando (tomography) experiments because it requires only a single intensity measurement. However, the phase information of the wave field is lost during the measurement and must be recovered. Conventional algebraic and iterative methods often rely on specific approximations or boundary conditions that may not be met by many samples or experimental setups. In addition, they require manual tuning of reconstruction parameters by experts, making them less adaptable for complex or variable conditions. Here we present a self-learning approach for solving the inverse problem of phase retrieval in the near-field regime of Fresnel theory using a single intensity measurement (hologram). A physics-informed generative adversarial network is employed to reconstruct both the phase and absorbance of the unpropagated wave field in the sample plane from a single hologram. Unlike most state-of-the-art deep learning approaches for phase retrieval, our approach does not require paired, unpaired, or simulated training data. This significantly broadens the applicability of our approach, as acquiring or generating suitable training data remains a major challenge due to the wide variability in sample types and experimental configurations. The algorithm demonstrates robust and consistent performance across diverse imaging conditions and sample types, delivering quantitative, high-quality reconstructions for both simulated data and experimental datasets acquired at beamline P05 at PETRA III (DESY, Hamburg), operated by Helmholtz-Zentrum Hereon. Furthermore, it enables the simultaneous retrieval of both phase and absorption information.

36 MATERIALS SCIENCE↗

NASA NTRS1982

Control concepts for the alleviation of windshears and gusts

Automatic control system design methods for gust and shear alleviation were studied. It is shown that automatic gust/shear alleviation systems can be quite effective if both throttle and elevator are used in harmony to produce the forces and moments required to counter the effects of the windshear. Regulation with respect to ground speed or airspeed results in very similar system designs. The application of the NASA total energy probe in the detection of windshear and criteria for alleviation is considered. The theory and application of robust output observers is extended. Design examples show how implementation of the control laws can be accomplished using observers, and thereby resulting in less complex control system configurations.

Rynaski, E. G.↗

NASA NTRS1986

A study of boiling heat transfer as applied to the cooling of ball bearings in the high pressure oxygen turbopump of the space shuttle main engine

Two sets of ball bearings support the main shaft within the High Pressure Oxygen Turbopump (HPOTP) in the Space Shuttle Main Engine (SSME). In operation, these bearings are cooled and lubricated with high pressure liquid oxygen (LOX) flowing axially through the bearing assembly. Currently, modifications in the assembly design are being contemplated in order to enhance the lifetime of the bearings and to allow the HPOTP to operate under larger loads. An understanding of the fluid dynamics and heat transfer characteristics of the flowing LOX is necessary for the implementation of these design changes. The proposed computational model of the LOX fluid dynamics, in addition to dealing with a turbulent flow in a complex geometry, must address the complication associated with boiling and two-phase flow. The feasibility of and possible methods for modeling boiling heat transfer are considered. The theory of boiling as pertains to this particular problem is reviewed. Recommendations are given for experiments which would be necessary to establish validity for correlations needed to model boiling.

Schreiber, Will↗

NASA NTRS1992

Calculation of Mg(+)-ligand relative binding energies

The calculated relative binding energies of 16 organic molecules to Mg(+) are compared with experimental results where available. The geometries of the ligands and the Mg(+)-ligand complexes arc optimized at the self-consistent field level using a 6-31G* basis set. The Mg(+) binding energies are evaluated using second-order perturbation theory and basis sets of triple-sigma quality augmented with two sets of polarization functions. This level of theory is calibrated against higher levels of theory for selected systems. The computed binding energies are accurate to about 2 kcal/mol.

Partridge, Harry↗

NASA NTRS1993

Theoretical Study of the H2-ML(+) Binding Energies

The cooperative ligand effects are studied in MLH2(+) and the results are compared to the recent experiments of Kemper et al. The bonding in these compounds is principally electrostatic in origin; however, ligand to metal and metal to ligand donations are important, especially for H2. We show that differences arise among the vanadium, cobalt, and copper complexes which are due to 3d donation to H2. Electron correlation is required to describe the dative interaction, and we find that second order Moller-Plesset perturbation theory (MP2) yields a good description of these systems compared with higher levels of correlation (such as the modified coupled pair functional and coupled cluster approaches) and experiment. However, obtaining quantitative results requires higher levels of theory than MP2.

Maitre, Philippe↗

NASA NTRS2001

Spatial/Spectral Identification of Endmembers from AVIRIS Data using Mathematical Morphology

During the last several years, a number of airborne and satellite hyperspectral sensors have been developed or improved for remote sensing applications. Imaging spectrometry allows the detection of materials, objects and regions in a particular scene with a high degree of accuracy. Hyperspectral data typically consist of hundreds of thousands of spectra, so the analysis of this information is a key issue. Mathematical morphology theory is a widely used nonlinear technique for image analysis and pattern recognition. Although it is especially well suited to segment binary or grayscale images with irregular and complex shapes, its application in the classification/segmentation of multispectral or hyperspectral images has been quite rare. In this paper, we discuss a new completely automated methodology to find endmembers in the hyperspectral data cube using mathematical morphology. The extension of classic morphology to the hyperspectral domain allows us to integrate spectral and spatial information in the analysis process. In Section 3, some basic concepts about mathematical morphology and the technical details of our algorithm are provided. In Section 4, the accuracy of the proposed method is tested by its application to real hyperspectral data obtained from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imaging spectrometer. Some details about these data and reference results, obtained by well-known endmember extraction techniques, are provided in Section 2. Finally, in Section 5 we expose the main conclusions at which we have arrived.

Plaza, Antonio↗

NASA NTRSDate not supplied

Hardware-Efficient Quantum Optimization Layered Algorithms and Experiments

Quantum optimization algorithms, such as QAOA, that implement parametrized stochastic optimization solvers attempt to identify low-energy solutions of Ising systems by exploiting available quantum effects in noisy-intermediate scale machines. Engineering a well-performing parametrized quantum optimization circuit is indeed an exercise in balancing the trade-off between expressivity and implementation complexity. We show that, for MaxCut QAOA circuits defined on native hardware topology (Rigetti’s Aspen Quantum Processors), error-mitigation techniques recover simulated features of the noiseless theory. Moreover, we explore a design space for QAOA-like ansatze that perform well in theory as well as in hardware for fully-connected problems. We also discuss how efficient coherence and entanglement detection methods that could be coupled with quantum optimization experiments require only linear overhead in benchmarking time.

quantum computing↗

DOE OSTI2026

Qudit Designs and Where to Find Them

Unitary t-designs are some of the most versatile tools in quantum information theory. Their applications range from randomized benchmarking and shadow tomography, to more fundamental ones such as emulating quantum chaos and establishing exponential separations between classical and quantum query complexity. While unitary designs originating from a group structure, such as the Clifford group, have proven to be incredibly useful for qubit systems, unfortunately, this is no longer true for qudits. In fact, the classification of finite-group representations rules out the existence of unitary 2-designs for arbitrary qudit dimensions. This severely limits the applicability of standard quantum information primitives when it comes to qudit systems. We overcome these limitations with a three-fold contribution. First, we introduce a general technique to construct families of weighted state t-designs in arbitrary qudit dimensions. These weighted state-designs generalize classical shadow tomography protocol from qubits to qudits. Second, we introduce a Clifford character RB that allows us to benchmark the qudit Clifford group in any dimension, including non-prime-power dimensions. And third, we establish bounds on the quantum circuit complexity of generating approximate unitary-designs from native gates in existing quantum hardware such as high-spin and cavity-QED qudits. Our work further highlights the analogy between spin and optical coherent states by proving that spin-GKP codewords form a state 2-design while spin coherent states do not; in direct analogy with the optical case. This work is structured as a pedagogical and self-contained introduction to unitary designs and their applications to qudit systems.

Anand, Namit [NASA, Ames; Unlisted, US] (ORCID:000↗

NASA NTRS2016

Augmenting Conceptual Design Trajectory Tradespace Exploration with Graph Theory

Within conceptual design changes occur rapidly due to a combination of uncertainty and shifting requirements. To stay relevant in this fluid time, trade studies must also be performed rapidly. In order to drive down analysis time while improving the information gained by these studies, surrogate models can be created to represent the complex output of a tool or tools within a specified tradespace. In order to create this model however, a large amount of data must be collected in a short amount of time. By this method, the historical approach of relying on subject matter experts to generate the data required is schedule infeasible. However, by implementing automation and distributed analysis the required data can be generated in a fraction of the time. Previous work focused on setting up a tool called multiPOST capable of orchestrating many simultaneous runs of an analysis tool assessing these automated analyses utilizing heuristics gleaned from the best practices of current subject matter experts. In this update to the previous work, elements of graph theory are included to further drive down analysis time by leveraging data previously gathered. It is shown to outperform the previous method in both time required, and the quantity and quality of data produced.

Dees, Patrick D.↗

NASA NTRS2016

Augmenting Conceptual Design Trajectory Tradespace Exploration with Graph Theory

Dees, Patrick D.↗

DOE OSTI2021

Modulating the Electron Affinity of Small Bipyridyl Molecules on Single Gold Nanoparticles for Plasmon-Driven Electron Transfer

Developing controlled platforms for plasmon-driven chemistry is of great importance in catalytic reactions at the nanoscale. We report anion radical formation for five bipyridyl complexes of varying degrees of electron affinity utilizing optically fo-cused intraband (594 nm) and interband (532 nm) pump excitation of single gold nanoparticles. The surface-enhanced Raman scattering (SERS) of anion radicals for the five non-resonant adsorbed molecules 2,2’-bipyridine (22BPY), 4,4’-bipyridine (44BPY), trans-1,2-bis(4-pyridyl)ethylene (BPE), 1,2-bis(4-pyridyl)acetylene (BPA), and 1,2-bis(4-pyridyl)ethane (BPEt) were detected using localized surface-plasmon resonance (LSPR) excitation with 785 nm. The electron affinity of the five bipyridyl complexes were determined using electrochemistry. Molecules with low electron affinity experienced high-er instances of radical anion formation under a plasmon-coupled intraband electron transfer excitation (594 nm) whereas molecules with high electron affinity showed a preference for anion radical formation under direct interband electron trans-fer excitation (532 nm). The lowest unoccupied molecular orbital (LUMO) energy levels for low electron affinity surface-bound molecules (22BPY, BPEt) are on average ~0.43 eV higher for high electron affinity surface-bound molecules (BPA, BPE, 44BPY) as calculated using time-dependent density functional theory, elucidating the importance of plasmon coupling to energy levels that facilitate charge transfer pathways. We also show the ability to ‘activate’ high vs low electron affinity single nanoparticles with the choice of pump excitation wavelength. The findings show the complex interplay between molecular electron affinity, orbital overlap with the density of states of the plasmonic metal, and excitation energetics of the pump laser wavelength. Potential applications of this work include enhanced control over molecular scale catalysis, biosensor design, and solar energy capture.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Tuning the optical and magnetic properties of lanthanide single-ion magnets using nitro-functionalized trispyrazolylborate ligands

We report the synthesis, crystal structures, photophysical and magnetic properties of 11 novel lanthanide complexes with the asymmetrically functionalized trispyrazolylborate ligand 4-nitrotrispyrazolylborate, 4-NO 2 Tp–: [Ln(4-NO 2 Tp) 3 ] (Ln = La–Dy, except Pm). In-depth photophysical characterization of the ligands via luminescence, reflectance and absorption spectroscopic techniques, decay lifetimes, quantum yields supported by time-dependent density functional theory (TD-DFT) and natural bond order (NBO) analysis reveal that n-NO 2 Tp– ligands are dominated by intra-ligand charge transfer (ILCT) transitions and that second-sphere interactions are critical to the stabilization of the T 1 state of n-NO 2 Tp– ligands and hence their ability to sensitize Ln 3+ emission. The luminescence properties of the complexes indicate that 4-NO 2 Tp– is a poor sensitizer of Ln 3+ emission, unlike 3-NO 2 Tp–. Moreover, [Nd(4-NO 2 Tp) 3 ] (crystallized as a hexane solvate) displays single-molecule magnet (SMM) properties, with longer relaxation times and larger barrier than the non-functionalized [NdTp 3 ], attributed to the addition of the NO 2 -group and subsequent rigidification of the molecular structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Combined density functional theory/kinetic Monte Carlo investigation of surface morphology during cycling of Li-Cu electrodes

In this work, we employed a combined density functional theory and kinetic Monte Carlo approach in order to investigate the nanoscale behavior of lithium stripping and plating on lithium-copper nanoalloys. Density functional theory calculations were used to develop an atom-by-atom understanding of the nucleation behavior of lithium on copper surfaces with different surface morphologies. We found that nanometric pits resulted in significantly more favorable lithium deposition when compared to pristine or lightly-defective Cu surfaces, which is in agreement with previous experimental studies. We then used density functional theory and constrained ab initio molecular dynamics to develop interaction and reaction parameters for a larger-scale kinetic Monte Carlo model in order to provide insight into the stripping and plating behavior of nanostructured Li-Cu nanoalloy anodes. Substantial losses in capacity and strong indications of morphological change were observed for a wide range of Cu:Li ratios over 100 cycles. We observed a complex relationship between the nanoparticle composition and the properties of the formed solid-electrolyte interphase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Matching Complexes of Trees and Applications of the Matching Tree Algorithm

A matching complex of a simple graph G is a simplicial complex with faces given by the matchings of G. The topology of matching complexes is mysterious; there are few graphs for which the homotopy type is known. Marietti and Testa showed that matching complexes of forests are contractible or homotopy equivalent to a wedge of spheres. We study two specific families of trees. For caterpillar graphs, we give explicit formulas for the number of spheres in each dimension and for perfect binary trees we find a strict connectivity bound. We also use a tool from discrete Morse theory called the Matching Tree Algorithm to study the connectivity of honeycomb graphs, partially answering a question raised by Jonsson.

97 MATHEMATICS AND COMPUTING↗