SEARCH · Search NASA

Results for “m:N”

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 181 records · Page 10

All sources NASA NTRS DOE OSTI

DOE OSTI2024

Soil Carbon and Nitrogen Stocks Across Hillslopes Underlain by Continuous Permafrost in the Northern Arctic Foothills, Alaska, United States

Constraining the variability of soil organic carbon (SOC) and total nitrogen (TN) stocks across hillslopes in Low Arctic permafrost-affected landscapes remains a significant challenge for improving global estimates of permafrost SOC stocks. We investigated SOC and TN stocks across hillslopes at two sites in the Arctic Foothills of Alaska, United States (Happy Valley and Sagwon Hills). Average SOC and TN stocks for the 0–1-m depth interval were high (52.0 ± 15.1 kg C m −2 and 2.74 ± 0.82 kg N m −2 ) and linearly related ( R 2 = 0.74, p < 0.0001). Unlike soils of other permafrost and nonpermafrost landscapes, variability was greatest within rather than between hillslope positions. Furthermore, SOC and TN stocks in the surface 1 m did not exhibit strong patterns by hillslope position and were only weakly associated with major geomorphic parameters that typically predict SOC and TN stocks well in other landscapes. Although sampling at upper hillslope positions was largely limited to depths of less than 1.5 m due to the presence of coarse fragments in reworked glacial till, deeper observations at lower hillslope positions (footslopes, toeslopes, and basins) revealed significantly larger SOC stocks (92.0 ± 18.0 kg C m −2 at 2 m; 117.1 ± 10.4 kg C m −2 at 3 m). The unique small-scale variability in ice content, cryoturbation, patterned ground, and organic layer thickness on these broad, Low Arctic sites contributes to the relatively homogeneous distribution of SOC and TN stocks across hillslope positions in the top 1 m, but a future focus on deeper sampling may reveal greater differences in SOC and TN stocks.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Improved Bounds for Burning Fence Graphs

Graph burning studies how fast a contagion, modeled as a set of fires, spreads in a graph. The burning process takes place in synchronous, discrete rounds. In each round, a fire breaks out at a vertex, and the fire spreads to all vertices that are adjacent to a burning vertex. Additionally, the burning number of a graph G is the minimum number of rounds necessary for each vertex of G to burn. We consider the burning number of the $m \times n$ Cartesian grid graphs, written $G_{m,n}$ . For $m = \omega (\sqrt{n})$ , the asymptotic value of the burning number of $G_{m,n}$ was determined, but only the growth rate of the burning number was investigated in the case $m = O(\sqrt{n})$ , which we refer to as fence graphs. We provide new explicit bounds on the burning number of fence graphs $G_{c\sqrt{n},n}$ , where $c > 0$ .

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

False positive PSMA PET for tumor remnants in the irradiated prostate and other interpretation pitfalls in a prospective multi-center trial

Readers need to be informed about potential pitfalls of [ 68 Ga]Ga-PSMA-11 PET interpretation. Here we report [ 68 Ga]Ga-PSMA-11 PET findings discordant with the histopathology/composite reference standard in a recently published prospective trial on 635 patients with biochemically recurrent prostate cancer. Consensus reads were false positive in 20 regions of 17/217 (8%) patients with lesion validation. Majority of the false positive interpretations (13 of 20, 65%) occurred in the context of suspected prostate (bed) relapse (T) after radiotherapy ( n = 11); other false positive findings were noted for prostate bed post prostatectomy (T, n = 2), pelvic nodes (N, n = 2), or extra pelvic lesions (M, n = 5). Major sources of false positive findings were PSMA-expressing residual adenocarcinoma with marked post-radiotherapy treatment effect. False negative interpretation occurred in 8 regions of 6/79 (8%) patients with histopathology validation, including prostate (bed) ( n = 5), pelvic nodes ( n = 1), and extra pelvic lesions ( n = 2). Lesions were missed mostly due to small metastases or adjacent bladder/urine uptake.[ 68 Ga]Ga-PSMA-11 PET at biochemical recurrence resulted in less than 10% false positive interpretations. Post-radiotherapy prostate uptake was a major source of [ 68 Ga]Ga-PSMA-11 PET false positivity. In few cases, PET correctly detects residual PSMA expression post-radiotherapy, originating however from treated, benign tissue or potentially indolent tumor remnants.

Radiology, Nuclear Medicine & Medical Imaging↗

DOE OSTI2021

Simulating Large PEPs Tensor Networks on Small Quantum Devices

We systematically map low bond dimension PEPs tensor networks to quantum circuits. By measuring and reusing qubits, we are in principle able to simulate an N×M square lattice PEPs network (for arbitrary M) of bond dimension 2 using N+ 2 qubits. We then seek to determine if this mapping can yield useful values for long-range loop observables in the presence of quantum device noise in the topological Wen plaquette model by mapping a 3×3 PEPs tensor network to a 5-qubit quantum circuit and executing it on the Honeywell System Model H1-1 trapped-ion device. We find that, for this system size, the noisy observable values are indeed sufficient for diagnosing topological vs. trivial order as the Wen model is perturbed by a magnetic field term in the Hamiltonian. We provide an overview of the experimental procedure and its results. We then explain in greater detail our method for mapping 2D tensor networks to quantum circuits and its scaling properties. This serves as a proof-of-concept of the utilty of the measure-and-reuse approach for simulating large 2D quantum systems on small quantum devices.

MacCormack, Ian↗

DOE OSTI2023

Computational framework for modeling of physical process

Techniques, systems, and devices are described for providing a computational frame for estimating high-dimensional stochastic behaviors. In one exemplary aspect, a method for performing numerical estimation includes receiving a set of measurements of a stochastic behavior. The set of correlated measurements follows a non-standard probability distribution and is non-linearly correlated. Also, a non-linear relationship exists between a set of system variables that describes the stochastic behavior and a corresponding set of measurements. The method includes determining, based on the set of measurements, a numerical model of the stochastic behavior. The numerical model comprises a feature space comprising non-correlated features corresponding to the stochastic behavior. The non-correlated features have a dimensionality of M and the set of measurements has a dimensionality of N, M being smaller than N. The method includes generating a set of approximated system variables corresponding to the set of measurements based on the numerical model.

Chen, Xiao↗

DOE OSTI2024

Computational framework for modeling of physical process

Chen, Xiao↗

DOE OSTI2020

Analytic and numerical bootstrap of CFTs with $O(m)\times O(n)$ global symmetry in 3D

Motivated by applications to critical phenomena and open theoretical questions, we study conformal field theories with O(m)\times O(n) O ( m ) × O ( n ) global symmetry in d=3 d = 3 spacetime dimensions. We use both analytic and numerical bootstrap techniques. Using the analytic bootstrap, we calculate anomalous dimensions and OPE coefficients as power series in \varepsilon=4-d ε = 4 − d and in 1/n 1 / n , with a method that generalizes to arbitrary global symmetry. Whenever comparison is possible, our results agree with earlier results obtained with diagrammatic methods in the literature. Using the numerical bootstrap, we obtain a wide variety of operator dimension bounds, and we find several islands (isolated allowed regions) in parameter space for O(2)\times O(n) O ( 2 ) × O ( n ) theories for various values of n n . Some of these islands can be attributed to fixed points predicted by perturbative methods like the \varepsilon ε and large- n n expansions, while others appear to arise due to fixed points that have been claimed to exist in resummations of perturbative beta functions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Symbol alphabets from plabic graphs

Symbol alphabets of n-particle amplitudes in N = 4 super-Yang-Mills theory are known to contain certain cluster variables of Gr(4, n) as well as certain algebraic functions of cluster variables. In this paper we suggest an algorithm for computing these symbol alphabets from plabic graphs by solving matrix equations of the form C ∙ Z = 0 to associate functions on Gr(m, n) to parameterizations of certain cells of Gr(k, n) indexed by plabic graphs. For m = 4 and n = 8 we show that this association precisely reproduces the 18 algebraic symbol letters of the two-loop NMHV eight-particle amplitude from four plabic graphs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Ground and excited electronic structures of electride and alkalide units: The cases of Metal-Tren, -Azacryptand, and -TriPip222 complexes

A systematic electronic structure analysis was conducted for M(L) n molecular electrides and their corresponding alkalide units M(L) n @M' (M/M' = Na, K; L = Tren, Azacryptand, TriPip222; n = 1, 2). All complexes belong to the “superalkali” category due to their low ionization potentials. The saturated molecular electrides display M+(L) n - form with a greatly diffuse quasispherical electron cloud. They were identified as “superatoms” considering the contours of populating atomic-type molecular orbitals. The observed superatomic Aufbau order of M(Tren) 2 is 1S, 1P, 1D, 1F, 2S, 2P, and 1G and it is consistent with those of M(Azacryptand) and M(TriPip222) up to the analyzed 1F level. Their excitation energies decrease gradually moving from M(Tren) 2 to M(Azacryptand) and to M(TriPip222). The studied alkalide complexes carry [M(L) n ] + @M' - ionic structure and their dissociation energies vary in the sequence of K(L) n @Na > Na(L) n @Na > K(L) n @K > Na(L) n @K. Similar to molecular electrides, the anions of alkalide units occupy electrons in diffuse Rydberg-like orbitals. In this work, excited states of [M(L) n @M'] 0/+/- and their trends are also analyzed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

A real-time energy and cost efficient vehicle route assignment neural recommender system

Here, this paper presents a neural network recommender system algorithm for assigning vehicles to routes based on energy and cost criteria. In this work, we applied this new approach to efficiently identify the most cost-effective medium and heavy duty truck (MDHDT) powertrain technology, from a total cost of ownership (TCO) perspective, for given trips. We employ a machine learning based approach to efficiently estimate the energy consumption of various candidate vehicles over given routes, defined as sequences of links (road segments), with little information known about internal dynamics, i.e. using high level macroscopic route information. A complete recommendation logic is then developed to allow for real-time optimum assignment for each route, subject to the operational constraints of the fleet. We show how this framework can be used to (1) efficiently provide a single trip recommendation with a top-k vehicles star ranking system, and (2) engage in more general assignment problems where n vehicles need to be deployed over m (m ≤ n) trips. This new assignment system has been deployed and integrated into the POLARIS. Transportation System Simulation Tool for use in research conducted by the Department of Energy's Systems and Modeling for Accelerated Research in Transportation (SMART) Mobility Consortium (SMART, 2024).

Energy consumption↗

DOE OSTI2025

On resistive interchange, double tearing, and resonant and non-resonant infernal modes in spherical tokamak negative central shear discharges

We examine the linear and nonlinear stability of a sequence of reversed shear NSTX equilibria with the same toroidal current density and pressure profile but with different toroidal field strengths. All equilibria have two q = 2 surfaces and have q > 1 everywhere. For this sequence, which all have β P ∼ 0.5, as the minimum value of q decreases below about 1.4, the localized resistive interchange criterion is strongly violated, and the unstable mode with toroidal mode number n=1 changes its dominant poloidal mode number m from a (m,n)=(2,1) double tearing mode to a non-resonant (1,1) infernal mode. This (1,1) mode nonlinearly flattens both the current density and the pressure near the magnetic axis. The higher-n unstable modes are all resistive infernal modes localized around the surface where q has a minimum and the magnetic shear vanishes. They generally saturate nonlinearly at low amplitude but can cause magnetic surface breakup near the axis.

Spitzer resistivity↗

DOE OSTI2025

Neural network-based classification and regression of magnetohydrodynamic modes in tokamaks

We present a machine learning-based magnetohydrodynamic (MHD) classifier and regressor that utilizes real or complex-valued 3D magnetic sensor array data to determine neoclassical tearing mode (NTM) onset times in tokamaks with millisecond accuracy. The input dataset consists of poloidal profiles of complex Fourier amplitudes with an n = 1 toroidal mode number from 144 human-labeled ITER Baseline Scenario discharges in the DIII-D tokamak, spanning both tearing-dominated and sawtooth-dominated regimes. Since m, n = 2,1 NTMs frequently emerge alongside sawteeth at the same frequency in this scenario, the focus is on isolating the m = 1 and m = 2 components of the n = 1 MHD mode near the tearing onset. To improve model regularization and prediction stability, singular value decomposition was applied to balance the sawtooth and tearing datasets. The enriched datasets facilitated training neural networks that learn the key distinguishing features of sawtooth and tearing modes in the poloidal profiles of their magnetic amplitude and phase. When the modes occur independently, the networks achieve perfect classification due to the modes’ distinct characteristics and low measurement noise. In the more experimentally relevant case where both modes coexist, the networks maintain exceptional performance across key metrics. Tests on synthetic data with known ground truth demonstrate the superior accuracy of the neural network trained on complex-valued input compared to models using real amplitude, phase, or pseudo-complex data, achieving both a mean time delay and standard deviation below 1 ms. Notably, standard linear regression methods fitting the dominant singular modes to the data closely match the neural network’s performance. Applying these methods across a broad range of H-mode scenarios will enable future studies to systematically identify dominant NTM triggers as scenario-specific variables, paving the way for more effective tearing mode avoidance strategies in future fusion reactor designs.

machine learning↗

DOE OSTI2020

Rational Design and Synthesis of Hierarchical Porous Mn–N–C Nanoparticles with Atomically Dispersed MnNx Moieties for Highly Efficient Oxygen Reduction Reaction

Developing transition-metal excluding iron and cobalt–nitrogen–carbon (M–N–C) electrocatalysts for the oxygen reduction reaction (ORR) is critical to substantially promote the development of precious-metal-free metal–air batteries and fuel cells. In the work, Mn–N–C nanoparticles with atomically dispersed MnNx moieties were synthesized by pyrolyzing Mn-ion–dual-pyridine coordinated complex, which was obtained via a simple condensation reaction between 2,6-diamino-pyridine and 2,6-diacetyl-pyridine with MnCl 2 as the Mn source. The precursor features with a characteristic structure of dual-pyridine ligand, which possesses a strong coordinating capability for Mn 2+ , facilitating the formation of highly dispersed nitrogen-coordinated Mn sites (MnN x ). Attributed to the highly active atomic MnN x sites, hierarchical pore structure, and high surface area of the Mn–N–C derived from the new precursor, it exhibits outstanding ORR performance in 0.1 M KOH with an almost direct four-electron reaction path and high selectivity of O 2 into H 2 O (low H2O2 production <3.5%). The half-wave potential of Mn–N–C is 0.88 V vs RHE, which is 20 mV higher than that of commercial Pt/C catalyst and reaches to the level of Fe–N–C catalyst obtained by the same method. Meanwhile, the feasibility of Mn–N–C for practical application is validated by its higher-performance power output in Zn–air battery with a maximum power density of 132 mW cm –2 compared to that of Pt/C (121 mW cm –2 ) using the same catalyst loading of 1.0 mg cm –2 . This work develops a convenient route to develop non-Fe or Co–N–C electrocatalyst for the ORR.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Single‐Atom Electrocatalysts from Multivariate Metal–Organic Frameworks for Highly Selective Reduction of CO 2 at Low Pressures

Abstract Single‐atom catalysts (SACs) are of great interest because of their ultrahigh activity and selectivity. However, it is difficult to construct model SACs according to a general synthetic method, and therefore, discerning differences in activity of diverse single‐atom catalysts is not straightforward. Herein, a general strategy for synthesis of single‐atom metals implanted in N‐doped carbon (M 1 ‐N‐C; M=Fe, Co, Ni and Cu) has been developed starting from multivariate metal–organic frameworks (MOFs). The M 1 ‐N‐C catalysts, featuring identical chemical environments and supports, provided an ideal platform for differentiating the activity of single‐atom metal species. When employed in electrocatalytic CO 2 reduction, Ni 1 ‐N‐C exhibited a very high CO Faradaic efficiency (FE) up to 96.8 % that far surpassed Fe 1 ‐, Co 1 ‐ and Cu 1 ‐N‐C. Remarkably, the best‐performer, Ni 1 ‐N‐C, even demonstrated excellent CO FE at low CO 2 pressures, thereby representing a promising opportunity for the direct use of dilute CO 2 feedstock.

Jiao, Long↗

DOE OSTI2025

Comparison of Ce( iv )/Th( iv )-alkynyl complexes and observation of a trans -influence ligand series for Ce( iv )

Organometallic cerium(iv) complexes have been challenging to isolate and characterize due to the strongly oxidizing nature of the cerium(iv) cation. Herein, we report two cerium(iv) alkynyl complexes, [Ce(TriNOx)(C[triple bond, length as m-dash]C-SiMe3)] (1-CeTMS) and [Ce(TriNOx)(C[triple bond, length as m-dash]C-Ph)] (1-CePh) (TriNOx3- = tris(2-tert-butylhydroxylaminato)benzylamine), that include terminal alkyne moieties. The isostructural thorium analogue [Th(TriNOx)(C[triple bond, length as m-dash]C-SiMe3)] (1-ThTMS) was also synthesized and compared with 1-CeTMS in bond distance, 13C-NMR spectra, vibrational spectra and electronic structure. The Ce-C bond distances were 2.501(3) Å for 1-CePh and 2.513(5) Å for 1-CeTMS on the shorter end of the few reported CeIV-C single bonds (2.478(3)-2.705(2) Å), possibly indicating significant Ce 5d- and 4f-orbital involvement. 13C-NMR spectroscopy was also consistent with Ce-C covalency, with significantly deshielded resonances ranging from 185-213 ppm. Such 13C-NMR shifts demonstrate a strong influence from spin-orbit coupling (SOC) effects, corroborated by computational studies. Raman analysis showed ν C[triple bond, length as m-dash]C stretching frequencies of 2000 cm-1 (1-CeTMS) and 2052 cm-1 (1-CePh), indicating the cerium(iv)-alkynyl interaction, compared to the parent HC[triple bond, length as m-dash]CPh (IR = 2105 cm-1 and Raman = 2104 cm-1). L3-edge X-ray absorption measurements revealed a predominant Ce(iv) electronic configuration, and magnetic measurements revealed temperature-independent paramagnetism. Electrochemical studies similarly revealed the electron donating ability of the alkynyl ligands, stronger than either fluoride or imido ligands for the Ce(iv)(TriNOx)-framework, with a cerium(iv/iii) reduction potential of E pc = -1.58 to -1.66 V vs. Fc/Fc+. Evidence for a trans-influence has been observed by evaluating a series including previously reported [CeIV(TriNOx)X]+/0 complexes with axial ligands X = THF, I-, Br-, Cl-, F-, -C[triple bond, length as m-dash]C-Ph, -C[triple bond, length as m-dash]C-SiMe3, -NH(3,5-(CF3)2-Ar), -OSiPh3, -N(M(L))(3,5-(CF3)2-Ar) [M(L) = Li(TMEDA), K(DME)2 or Cs(2,2,2-crypt)]. These data stand in contrast with previous reports of an inverse trans-influence at cerium(iv) and point to differences in involvement of cerium 4f- versus 5d-orbitals in the electronic structures of the complexes.

Yang, Qiaomu↗

DOE OSTI2022

Dimension-adaptive machine learning-based quantum state reconstruction

Here, we introduce an approach for performing quantum state reconstruction on systems of n qubits using a machine learning-based reconstruction system trained exclusively on m qubits, where m ≥ n. This approach removes the necessity of exactly matching the dimensionality of a system under consideration with the dimension of a model used for training. We demonstrate our technique by performing quantum state reconstruction on randomly sampled systems of one, two, and three qubits using machine learning-based methods trained exclusively on systems containing at least one additional qubit. The reconstruction time required for machine learning-based methods scales significantly more favorably than the training time; hence this technique can offer an overall saving of resources by leveraging a single neural network for dimension-variable state reconstruction, obviating the need to train dedicated machine learning systems for each Hilbert space.

42 ENGINEERING↗

DOE OSTI2020

Tailoring Electronic and Optical Properties of MXenes through Forming Solid Solutions

Abstract not provided

Han, Meikang↗

DOE OSTI2026

Positional Isomer of P3HB by Stereoselective Polymerization of Racemic α-Methyl-β-propiolactone Delivers Polyethylene-like Properties

Biobased and biodegradable poly(3-hydroxybutyrolactone) (P3HB) has long been considered as a more sustainable alternative to petroleum-based, nonbiodegradable polyolefins, but its properties are far off from its polyolefin (polyethylene, PE, and polypropylene, PP) counterpart’s unique set of thermal (low T g below −20 °C and high T m > 100 °C) and mechanical (high ductility >350%) characteristics. Here, we report that a positional isomer of P3HB, poly(3-hydroxy-2-methylpropionate) (P3H2MP), synthesized by catalyst-controlled stereoselective polymerization of racemic α-methyl-β-propiolactone, can match that demanding set of thermomechanical properties of PE. In particular, isotactic-rich P3H2MP, readily synthesized under ambient conditions, reaches high M n close to one million Da, T g down to −25 °C, T m up to 115 °C, tensile strength up to 64 MPa, and toughness up to 131 MJ m –3 , thus mechanically outperforming PE while maintaining a comparable low T g and high T m combination. A P3H2MP-based triblock copolymer further widens the low-high temperature window from T g = −29 °C to T m = 186 °C, resembling those of PP. These results show that P3H2MP exhibits the unique combination of thermomechanical properties matching those of high-performance polyolefins.

Biopolymers↗