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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 631 records · Page 35

On the Prospect of Chemically Transferable Coarse-Grained Electronic Models for Soft Materials

Electronic coarse-graining (ECG) methods predict quantum-mechanical electronic properties directly from coarse-grained (CG) molecular configurations, enabling electronic predictions at mesoscale length scales. Here, we present a diagnostic assessment of the feasibility of chemically transferable ECG models across a broad polymer-relevant chemical space using all-atom, united-atom, and Martini-scale representations. While high-resolution ECG models achieve near-quantitative accuracy, we show that chemically transferable ECG at the Martini resolution fails because the CG force field does not sample the same configurational distribution of local molecular structure as that underlying the DFT-parameterized ECG model. We demonstrate that our proposed Element-Count-Label (ECL) representation, which augments Martini beads with explicit stoichiometric data, significantly improves chemical generalization across diverse polymer chemistries. However, we find that even with improved chemical resolution, the model cannot recover electronic property distributions that are absent from the configurational space sampled by the CG force field. These results demonstrate that chemically transferable ECG requires future Martini-like force fields to explicitly preserve quantum chemistry–compatible local molecular structure in addition to thermodynamic and structural fidelity.

Kidder, Katherine M [Department of Chemistry; Univ↗

Superconductivity and Local Inversion-Symmetry Breaking

Inversion and time reversal are essential symmetries for the structure of Cooper pairs in superconductors. The loss of one or both leads to modifications to this structure and can change the properties of the superconducting phases in profound ways. Superconductivity in materials lacking inversion symmetry, or noncentrosymmetric materials, has become an important topic. These materials show unusual magnetic and magnetoelectric properties and can host topological superconductivity. Recently, crystal structures with local, but not global, inversion-symmetry breaking have attracted attention. Here, superconductivity can exhibit phenomena not naively expected in centrosymmetric materials. In this review, we first introduce the concept of locally noncentrosymmetric crystals and different material realizations. We then discuss consequences of such local symmetry breaking on the normal state electronic structure and the classification of superconducting order parameters. Finally, we review the expected and, in parts, already observed phenomenology of unconventional superconductivity and possible topological superconducting phases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Role of backbone strain in de novo design of complex α/β protein structures

Abstract We previously elucidated principles for designing ideal proteins with completely consistent local and non-local interactions which have enabled the design of a wide range of new αβ-proteins with four or fewer β-strands. The principles relate local backbone structures to supersecondary-structure packing arrangements of α-helices and β-strands. Here, we test the generality of the principles by employing them to design larger proteins with five- and six- stranded β-sheets flanked by α-helices. The initial designs were monomeric in solution with high thermal stability, and the nuclear magnetic resonance (NMR) structure of one was close to the design model, but for two others the order of strands in the β-sheet was swapped. Investigation into the origins of this strand swapping suggested that the global structures of the design models were more strained than the NMR structures. We incorporated explicit consideration of global backbone strain into the design methodology, and succeeded in designing proteins with the intended unswapped strand arrangements. These results illustrate the value of experimental structure determination in guiding improvement of de novo design, and the importance of consistency between local, supersecondary, and global tertiary interactions in determining protein topology. The augmented set of principles should inform the design of larger functional proteins.

59 BASIC BIOLOGICAL SCIENCES↗

Probing the Kinetic Origin of Varying Oxidative Stability of Ethyl- vs. Propyl-spaced Amines for Direct Air Capture

Amine-based adsorbents are promising for direct air capture of CO 2 , yet oxidative degradation remains a key unmitigated risk hindering wide-scale deployment. Borrowing wisdom from the basic auto-oxidation scheme, insights are gained into the underlying degradation mechanisms of polyamines by quantum chemical, advanced sampling simulations, adsorbent synthesis, and accelerated degradation experiments. The reaction kinetics of polyamines are contrasted with that of typical aliphatic polymers and they elucidate for the first time the critical role of aminoalkyl hydroperoxide decomposition in the oxidative degradation of amino-oligomers. The experimentally observed variation in oxidative stability of polyamines with different backbone structures is explained by the relationship between the local chemical structure and the free energy barrier of aminoalkyl hydroperoxide decomposition, suggesting that its energetics can be used as a descriptor to screen and design new polyamines with improved stability. In conclusion, the developed computational capability sheds light on radical-induced degradation chemistry of other organic functional materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Galactic ArchaeoLogIcaL ExcavatiOns (GALILEO) II. t-SNE portrait of local fossil relics and structures

Based on high-quality Apache Point Observatory Galactic Evolution Experiment (APOGEE) DR17 and Gaia DR3 data for 1742 red giants stars within 5 kpc of the Sun and not rotating with the Galactic disk (V φ < 100 km s -1 ), we used the nonlinear technique of unsupervised analysis t-Distributed Stochastic Neighbor Embedding (t-SNE) to detect coherent structures in the space of ten chemical-abundance ratios: [Fe/H], [O/Fe], [Mg/Fe], [Si/Fe], [Ca/Fe], [C/Fe], [N/Fe], [Al/Fe], [Mn/Fe], and [Ni/Fe]. Additionally, we obtained orbital parameters for each star using the nonaxisymmetric gravitational potential GravPot16. Seven structures are detected, including Splash, Gaia-Sausage-Enceladus (GSE), the high-α heated-disk population, N-C-O peculiar stars, and inner disk-like stars, plus two other groups that did not match anything previously reported in the literature, here named Galileo 5 and Galileo 6 (G5 and G6). These two groups overlap with Splash in [Fe/H], with G5 having a lower metallicity than G6, and they are both between GSE and Splash in the [Mg/Mn] versus [Al/Fe] plane, with G5 being in the α-rich in situ locus and G6 on the border of the α-poor in situ one. Nonetheless, their low [Ni/Fe] hints at a possible ex situ origin. Their orbital energy distributions are between Splash and GSE, with G5 being slightly more energetic than G6. We verified the robustness of all the obtained groups by exploring a large range of t-SNE parameters, applying it to various subsets of data, and also measuring the effect of abundance errors through Monte Carlo tests.

79 ASTRONOMY AND ASTROPHYSICS↗

Elucidating the local atomic and electronic structure of amorphous oxidized superconducting niobium films

Qubits made from superconducting materials are a mature platform for quantum information science application, such as quantum computing. However, material-based losses are now a limiting factor in reaching the coherence times needed for applications. In particular, knowledge of the atomistic structure and properties of the circuit materials is needed to identify, understand, and mitigate material-based decoherence channels. Here, we characterize the atomic structure of the native oxide film formed on Nb resonators by comparing fluctuation electron microscopy experiments to density functional theory calculations, finding that an amorphous layer is consistent with an Nb 2 O 5 stoichiometry. Comparing x-ray absorption measurements at the Oxygen K edge with first-principles calculations, we find evidence of d-type magnetic impurities in our sample, known to cause impedance in proximal superconductors. This work identifies the structural and chemical composition of the oxide layer grown on Nb superconductors and shows that soft x-ray absorption can fingerprint magnetic impurities in these superconducting systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Mesoscale Investigation of Dislocation-Grain Boundary Interactions in Metals and Alloys [Slides]

GBs have been subject of intense study for several years, including the effects of microstructure on mechanical response. Until recently these have been primarily focused on a limited number of idealized GB structures (i.e, the minimum energy structure). We are specifically focusing on changes in local GB structure and the effect this has on dislocation-grain boundary interactions. This will help us to better understand both (more) realistic and general GB structures.

36 MATERIALS SCIENCE↗

Additively manufactured locally resonant interpenetrating lattice structure

A method and apparatus for attenuating acoustic waves is provided. A lattice is formed with a plurality of support struts. A plurality of resonating struts are formed extending between the support struts, wherein the resonating struts are configured to attenuate acoustic waves within a predetermined range of frequencies while allowing acoustic waves outside the predetermined range of frequencies to pass through the resonant structure unattenuated. The resonant structure is interposed between two bodies to isolate one body from acoustic waves from the other body over the predetermined range of frequencies.

Hammetter, Chris↗

A transfer learning approach for acoustic emission zonal localization on steel plate-like structure using numerical simulation and unsupervised domain adaptation

The detection and localization of damage in metallic structures using acoustic emission (AE) monitoring and artificial intelligence technology such as deep learning has been widely studied. However, a current challenge of this approach is the difficulty of obtaining sufficient labeled historical AE signals for the training process of deep learning models. This problem can be approached through the implementation of transfer learning. The innovation of this paper lies in the development of a transfer learning approach for AE source localization on a stainless-steel structure when no historical labeled AE signals are available for training. A finite element model is developed to generate numerical AE signals for the training. Unsupervised domain adaptation (UDA) technology is utilized to reduce the distribution difference between the numerical and the realistic AE signals and to derive the localization results of the unlabeled realistic AE signals. Finally, the results suggest that the proposed approach is capable of localizing AE signals with high accuracy in the absence of labeled training data.

42 ENGINEERING↗

Structural and physical properties of Ni 1- x V x alloys around and away from quantum critical point

We investigate the room temperature structure (global and local), temperature dependent magnetic and transport behaviour of Ni 1-x V x (0$&LessSlantEqual;$x$ &LessSlantEqual;$ $0.13$) alloys. Our Energy Dispersive Analysis of x-rays results show that the prepared compositions are stoichiometric. With increase in V doping, the compounds exhibit a quantum phase transition around x c = 0.12, where the ferromagnetic phase is suppressed. Further, our results show that all the compounds stabilize in face centred cubic structure at RT and the lattice parameter shows unusual behaviour close to x c . The magnetic and heat capacity studies show signature of Griffiths phase on either side of x c . From 25 K to the lowest collected temperature, we observe a linear T dependence of resistivity at x = 0.1 and around x c , which is separated by a Fermi-liquid region around x = 0.106. This suggests that the origin of the transport behaviour is different around the quantum critical point and away from it. Our Ni K-edge x-ray Absorption Spectroscopy results show that there is a significant reduction in the first coordination number around Ni central atom on doping. Further, with doping, there is distortion in the first coordination shell around Ni. This suggests, with V doping, the local structure around Ni is different from the global structure as obtained from the x-ray Diffraction results. Interestingly, with doping, we observe a direct connection between the extent of distortion at RT and the magnetic disorder obtained at 2 K. We believe our results will motivate the scientific community to further study the interplay between the structural disorder and quantum fluctuations with temperature at the local level.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Harnessing Neural Networks for Elucidating X-ray Absorption Structure–Spectrum Relationships in Amorphous Carbon

Improved understanding of structural and chemical properties through local experimental probes, such as X-ray absorption near-edge structure (XANES) spectroscopy, is crucial for the understanding and design of functional materials. In recent years, significant advancements have been made in the development of data science approaches for the automated interpretation of XANES structure–spectrum relationships. However, existing studies have primarily focused on crystalline solids and small molecules, while fewer efforts have been devoted to disordered systems. Thus, in this work, we demonstrate the development of neural network models for predicting and interpreting XANES spectra of amorphous carbon (a-C) from local structural descriptors. Comparison between different structural descriptors expectedly shows that the inclusion of both bond length and bond angle information is necessary for an accurate prediction of the spectra. Among the descriptors considered in this work, we find that the local many-body tensor representation yields the highest accuracy and greatest interpretability so that it can be leveraged to understand the importance of structural motifs in determining XANES spectra. Furthermore, we also discuss performance of neural network models for predicting both local structure features, such as bond lengths and bond angles, and global chemical composition, such as the sp:sp 2 :sp 3 ratio.

36 MATERIALS SCIENCE↗

Associating damage nucleation and distribution with grain boundary characteristics in Ta

Here, the effect of grain boundary (GB) characteristics (as represented by misorientation angle) on its dynamic response is investigated by sampling a large set of 185 GBs in Ta bi-crystals. These GBs encompass both ordered and disordered structures – typically referred to as metastable structures, in order to reflect the diversity in the local atomic structure observed in realistic GBs. The results reveal four distinct regimes in damage distribution and failure modes as a function of misorientation angle. The above trends also correlate with the variation in the corresponding void nucleation stress.

36 MATERIALS SCIENCE↗

Hierarchical-embedding autoencoder with a predictor as efficient architecture for learning time-evolution in multi-scale turbulent flows

We introduce a scale-aware, data-driven deep learning modeling framework for accurately predicting the time evolution of multi-scale turbulent plasma and liquid flows. The approach is motivated by the idea of scale separation. Structures of vastly different length scales emerge in these systems, and interactions between these structures occur only locally. To exploit this structure, the flow state is transformed by a hierarchical, fully convolutional autoencoder, not into a single embedding layer as in conventional convolutional surrogate models, but into a series of embedding layers. A stepwise training strategy ensures that fine-scale features are encoded on a high-resolution grid, while larger structures are represented on progressively coarser layers. The time evolution predictor advances all embedding layers in sync, capturing local interactions between features at the same scale as well as between all scales. This approach enables efficient modeling of multi-scale systems since negligible interactions between distant, small-scale structures do not need to be directly modeled. Our hierarchical-embedding autoencoder with a predictor framework is evaluated on canonical examples of multi-scale turbulence: two-dimensional Kolmogorov flow and Hasegawa–Wakatani plasma turbulence. In both cases, the proposed framework significantly improves predictive accuracy relative to conventional convolutional network architectures. A significant improvement in prediction accuracy was observed for crucial statistical characteristics of the Hasegawa–Wakatani plasma as well as for individual trajectories of the Kolmogorov flow turbulence. Importantly, the model's rollout for the Hasegawa–Wakatani problem demonstrates a four-order-of-magnitude speedup compared to traditional numerical solvers.

Khrabry, Alexander I. [Princeton Univ., NJ (United↗

Small angle X-ray studies of short-range order in non-stoichiometric pseudoprotic ionic liquids: the influence of chemical structure

Mixtures of organic acids and amines have been studied extensively owing to their unusual physicochemical properties and applications as solvents for extraction. In equimolar ratios they represent pseudoprotic ionic liquids, and in other, “nonstoichiometric” ratios they display a range of odd physicochemical behaviors. We report the results of small-angle X-ray scattering studies of a series of such systems with a range of chemical structures chosen to explore the link between molecular geometry and the character of the emergent nanoscale local liquid structure. We find that while the details vary, structure can emerge even when the hydrogen-bonding character of the components is changed significantly, and the character of their hydrocarbon substituents is altered. The consistent emergence of local order in the face of varying chemical structures indicates that the process is robust. Furthermore, this implies that the emergence of such structure may in fact be far more common in liquid mixtures than is currently recognized, and a great many structures may be suitable for the synthesis of pseudoprotic ionic liquids.

77 NANOSCIENCE AND NANOTECHNOLOGY↗