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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 433 records · Page 24

Structural transitions in the GTP cap visualized by cryo-electron microscopy of catalytically inactive microtubules

Microtubules (MTs) are nonequilibrium polymers that switch between states of growth and shrinkage. This property is critical for their function and is a consequence of GTP hydrolysis in the MT. The structure of the stable GTP part of the MT (the GTP cap) has previously been inferred from MTs polymerized with nonhydrolyzable GTP analogs. Here, we report high-resolution structures of MTs truly containing GTP, polymerized from mutated, hydrolysis-deficient tubulins. We find that GTP-MTs have an “expanded lattice” and a “closed seam,” structural characteristics possibly responsible for stabilizing the GTP cap. These results provide insight into the structural transitions at growing MT ends, furthering our understanding of the bistable nature of MTs.

59 BASIC BIOLOGICAL SCIENCES↗

High-resolution cryo-electron microscopy structure of photosystem II from the mesophilic cyanobacterium, Synechocystis sp. PCC 6803

Significance Photosystem II (PSII) is a photo-oxidoreductase that harnesses light energy to use water to make fuel. Water oxidation occurs at a metal cluster in the active site called the oxygen-evolving complex (OEC). Understanding PSII function has provided design principles for synthetic solar fuel catalysts; however, the details of water oxidation are obscured by the multiple states through which the mechanism proceeds, differences between species, and lability of the OEC. To better understand PSII function, we solved its structure from Synechocystis sp. PCC 6803. We observe significant differences compared with PSII from thermophilic cyanobacteria that highlight the need for reexamination of previous data using this structure for interpretation. The structure also provides a platform for studies of site-directed mutations of PSII.

PsbV↗

Machine Learning-Enabled Image Classification for Automated Electron Microscopy

Abstract Traditionally, materials discovery has been driven more by evidence and intuition than by systematic design. However, the advent of “big data” and an exponential increase in computational power have reshaped the landscape. Today, we use simulations, artificial intelligence (AI), and machine learning (ML) to predict materials characteristics, which dramatically accelerates the discovery of novel materials. For instance, combinatorial megalibraries, where millions of distinct nanoparticles are created on a single chip, have spurred the need for automated characterization tools. This paper presents an ML model specifically developed to perform real-time binary classification of grayscale high-angle annular dark-field images of nanoparticles sourced from these megalibraries. Given the high costs associated with downstream processing errors, a primary requirement for our model was to minimize false positives while maintaining efficacy on unseen images. We elaborate on the computational challenges and our solutions, including managing memory constraints, optimizing training time, and utilizing Neural Architecture Search tools. The final model outperformed our expectations, achieving over 95% precision and a weighted F-score of more than 90% on our test data set. This paper discusses the development, challenges, and successful outcomes of this significant advancement in the application of AI and ML to materials discovery.

Materials Science↗

Stable Photoemission from the Wehnelt Aperture Surface in 4D Ultrafast Electron Microscopy

Here we show that photoemission with high long-term stability that is immediate and robust can be generated from the surface of the Wehnelt aperture in a TEG-based UEM. Further, we show that the resulting photobeam quality can be at least as good as that from LaB 6 , whether under photo or thermionic operation. We hypothesize that the energy distribution and the temporal properties of the beam are improved relative to LaB 6 owing to the closer match of photon energy to aperture work function.

36 MATERIALS SCIENCE↗

Revealing Possible Coherence Limiting Sources in Superconducting Qubit with Advanced Electron Microscopy

Superconducting materials hold great potential for solid-state quantum computing. Their fabrication relies on established semiconductor fabrication techniques, such as thin film deposition and lithography, but the complex processing steps can result in defects at the qubits' interfaces and surfaces that can negatively impact coherence time. To improve superconducting qubit performance, it is essential to understand the structural features, at the atomic scale, that may act as sources of decoherence limiting factor in both the Josephson junction (JJ) and resonators, which are key components of superconducting qubit. This talk will present our recent studies on the microstructures in a 2D-transmon, with an emphasis on the JJ. For this research, a combination of advanced microscopy techniques, including high-resolution (S)TEM imaging, and spectroscopy (EDS and EELS) are used to identify possible coherence-limiting defects or structural features.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Enhancing Electron Microscopy Image Classification Using Data Augmentation

Manual labeling for machine learning tasks such as image classification is tedious and labor-intensive; as a result, scientific datasets suitable for deep learning applications are scarce and limited. While data augmentation techniques have shown promise for extending image datasets, very little work has been done to understand the impact of combining multiple augmentation methods sequentially or the limits of their effectiveness when combined. Our work addresses this gap by examining how standard and combinatorial data augmentation affects the performance of machine learning models when trained on small datasets for label classification tasks. For our analysis, we generate single, double and quadruple-augmented datasets for a microscopy image classification task using six standard augmentation methods, and compare the resultant improvements observed in binary classification accuracy with three standard image classification models (DenseNet169, MobileNetV2, ResNet101V2). Our experiments show a non-monotonic relationship between the number of simultaneous augmentation methods and classification accuracy, indicating that there is a trade-off between the degree of augmentation and the model performance. These findings suggest that the optimal number of augmentation methods will vary by domain and use case. We also find that the order in which augmentation methods are applied to a limited dataset matters when combining augmentation schemes, with our use case showing performance differences up to 2.6% when the augmentation order is reversed for double-augmented datasets. Our work offers insights to the limits of data augmentation when working on image classification tasks with limited datasets.

Welsman, Jordan A↗

Ta–Zr carbides: Synthesis advances via carbothermal reduction and defect evolution observed through transmission electron microscopy ion irradiation

The thermodynamic stability of six distinct compositions within the Zr—Ta—C ternary system is investigated in this study, marking the first report of their synthesis through carbothermic reduction in vacuum. A prolonged annealing process at 2200°C enabled high densification and phase equilibrium. Detailed phase identification and microstructural characterization through microscopy and X-ray diffraction techniques revealed clear compositional trends and stable phase formations. Two compositions ((Ta 0.2 Zr 0.8 )C 0.6 and (Ta 0.5 Zr 0.5 )C 1 ) were selected for ion irradiation experiments using 200 keV Kr + at 600°C—representing the first-ever irradiation study on the Zr—Ta—C system. The findings indicated defect accumulation and nanoscale cavity formation without any evidence of amorphization, highlighting the system's structural stability under irradiation. Together, the synthesis and irradiation results provide a basis for further investigation of the system and suggest its relevance for applications under extreme environments.

36 MATERIALS SCIENCE↗