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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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Atomic defects, functional groups and properties in MXenes
MXenes, a new family of functional two-dimensional (2D) materials, have shown great potential for an extensive variety of applications within the last decade. Atomic defects and functional groups in MXenes are known to have a tremendous influence on the functional properties. In this review, we focus on recent progress in the characterization of atomic defects and functional group chemistry in MXenes, and how to control them to directly influence various properties ( e.g ., electron transport, Li + adsorption, hydrogen evolution reaction (HER) activity, and magnetism) of 2D MXenes materials. Dynamic structural transformations such as oxidation and growth induced by atomic defects in MXenes are also discussed. The review thus provides perspectives on property optimization through atomic defect engineering, and bottom-up synthesis methods based on defect-assisted homoepitaxial growth of MXenes.
The synergistic effects of central core size and end group engineering on performance of narrow bandgap nonfullerene acceptors
Understanding the relationship between the molecular structure and photoelectric properties of fused-ring non-fullerene acceptors (NFAs) is of far-reaching significance to the development of organic solar cells (OSCs). Herein, six NFAs based on multiple thiophenes (4 T, 6 T and 8 T) are employed to systematically probe the synergistic effects of extending central core size and terminal fluorination. The absorption results manifest that the molecular absorption is comprehensively affected by molecular crystallinity, planarity, conjugation length and intramolecular electron push–pull effect, simultaneously. The intensity of electron push–pull effect is not only related to the electron-donating ability of central core and the electron-withdrawing ability of end group, but also may be related to the distance between the positive and negative centers. The extension of central core leads to the more planar backbone and stronger crystallinity of NFAs, and less energy loss (E loss ) in its based OSC. Compared with the extension of central core, terminal fluorination has a greater impact on molecular photoelectric properties. The terminal fluorination significantly enhances the push–pull effect, lowers the energy levels, and slightly increases the vibrational relaxation. As a result, the strongest crystallinity and coplanarity of 8TIC-4F lead to a low vibrational relaxation of 0.18 eV, which makes PTB7-Th:8TIC-4F device exhibit a small E loss of 0.51 eV and a high efficiency of 10.4%. In addition, the fluorinated 6TIC-4F with suitable core size exhibits suitable energy level, absorption, crystallization, and phase separation morphology, making its as-cast device up to 11.61% efficiency. Finally, to the best of the authors’ knowledge, the PCE of 11.61% for PTB7-Th:6TIC-4F based device without any treatment is one of the highest values reported for the NAFs with over 1000 nm absorption.
Promoting reversibility of layered potassium cathode through interstitial doping
With the increasing needs for large-scale and low-cost energy storage devices, Mn-based layered oxide cathodes have achieved considerable researching interests for potassium-ion batteries owing to their high energy density, abundant resource and low toxicity. However, their developments are challenged by the absence of suitable cathode materials to tolerate large-sized K-ion insertion/extraction and the presence of Jahn-Teller distortion of Mn 3+ . To address this issue, here we present a strategy of embedding boron into interstitial tetrahedral sites to obtain a P3-K 0.5 Mn 0.8 Co 0.2 B 0.1 O 2 cathode. Strong B-O covalent bonds facilitate the construction of robust orthorhombic framework and alleviate the undesired elongation of Mn-O bonds, contributing to excellent electrochemical performance. In addition, boron ions are verified to promote the formation of a homogeneous cathode electrolyte interphase layer, improving interfacial stability and realizing highly reversible cycling in a wide voltage range (1.4-4.3 V). This strategy provides a new pathway towards the development of high-performance cathode materials for potassium-ion batteries.
Microsphere LiMn 0.6 Fe 0.4 PO 4 /C cathode with unique rod-like secondary architecture for high energy lithium ion batteries
LiMn x Fe 1-x PO 4 /C is considered a promising next-generation cathode material with significant commercial potential, inheriting the safety of LiFePO 4 while offering higher energy densities. However, the extremely low conductivity and the Jahn-Teller effect induced by Mn 3+ limit its practical capacity and rate performance. Effective modifications can be achieved through particle nanonization and uniform carbon coating. Here, in this work, we synthesized microspherical LiMn 0.6 Fe 0.4 PO 4 /C cathode materials using a hydrothermal method combined with spray drying carbon coating. The cathode material exhibits a microsphere structure composed of aggregated nanorods with a uniform 3 nm carbon coating, showing good dispersibility, small specific surface area and high tap density. In-situ diffraction analysis showed that expanding the single-phase solid solution region during (de)lithiation can reduce the energy barrier for electron transport, improve the kinetics of the (dis)charge process, and enhance both cycling and rate performance. The initial capacity at 0.1C can reach 155 mAh/g, and the capacity remains at 133.5 mAh/g with a retention rate of 97.1 % after 300 cycles. The synergistic effect of particle nanonization and uniform carbon coating endows the LiMn x Fe 1-x PO 4 /C material with excellent electrochemical performance.
Proteogenomic Characterization of Endometrial Carcinoma
We undertook a comprehensive proteogenomic characterization of 95 endometrial carcinomas, of which 83 were endometrioid tumors and 12 were serous tumors. This analysis revealed new consequences of perturbations to the p53 and Wnt/ß-catenin pathways, identified a potential role for circRNAs in the epithelial-mesenchymal transition, and provided new insights into proteomic markers of clinical and genomic tumor subgroups, some of which are in known druggable pathways. We performed a broad genome-wide acetylation survey, one of the first of its kind, yielding insights into regulatory mechanisms of histone acetylation. We also characterized the tumor immune landscape, including immunogenic alterations, neoantigens, common cancer/testis antigens, and the immune microenvironment, all of which can inform immunotherapy decisions. Collectively, our multi-omic analyses provide a valuable resource for researchers and clinicians, further our understanding of the molecular mechanisms underlying endometrial carcinoma, and identify new avenues for investigating potential therapeutic targets.
Pan-cancer proteogenomics characterization of tumor immunity
Despite the successes of immunotherapy in cancer treatment over recent decades, less than <10%–20% cancer cases have demonstrated durable responses from immune checkpoint blockade. To enhance the efficacy of immunotherapies, combination therapies suppressing multiple immune evasion mechanisms are increasingly contemplated. To better understand immune cell surveillance and diverse immune evasion responses in tumor tissues, we comprehensively characterized the immune landscape of more than 1,000 tumors across ten different cancers using CPTAC pan-cancer proteogenomic data. We identified seven distinct immune subtypes based on integrative learning of cell type compositions and pathway activities. We then thoroughly categorized unique genomic, epigenetic, transcriptomic, and proteomic changes associated with each subtype. Further leveraging the deep phosphoproteomic data, we studied kinase activities in different immune subtypes, which revealed potential subtype-specific therapeutic targets. Insights from this work will facilitate the development of future immunotherapy strategies and enhance precision targeting with existing agents.
Prehydration of calcium sulfoaluminate (CSA) clinker at different relative humidities
The use of CSA cement in practice has been hindered by its unstable performance and short shelf-life caused by the prehydration of CSA clinker. In this study, the effect of ambient humidity on the prehydration rate and process of CSA clinker was investigated. The prehydration degree, ageing progress, and the dynamic change of mineral composition of CSA clinker exposed to five different relative humidities (ranging from 23% to 98%) for up to 180 days were studied. Experiments revealed that the ambient humidity of 60% RH can be considered a threshold value for storage of CSA clinker. Exposure of CSA clinker to RH higher than 60% will not only result in a significant decrease of hydraulic reactivity, but also in agglomeration of the clinker. Although the exposure of CSA clinker to RH lower than 60% has little effect on the hydraulic reactivity, the main hydration peak was found to be slightly delayed with the increase of RH.
Advantages of tandem versus simultaneous operation: The case of isomerization/hydrogenation of terpinolene epoxide to Terpinen-4-ol using a Ni/TiO 2 -SiO 2 bifunctional catalyst
The conversion of terpinolene epoxide to terpinen-4-ol is a desirable chemical transformation for the production of a valuable intermediate. Here this report describes a one-pot, two-step system for the reaction that uses a bifunctional Ni/TiO 2 -SiO 2 catalyst with isomerization and hydrogenation capabilities. The TiO 2 -SiO 2 serves to isomerize the starting epoxide. The Ni component works to hydrogenate the allylic double bond. The tandem system achieves a high 64% yield of terpinen-4-ol. X-ray diffraction analysis showed that TiO 2 -SiO 2 was a mixed binary oxide, and Fourier transform infrared spectroscopy of adsorbed pyridine suggested that acid sites were mainly Lewis acid sites. Electron microscopy showed that the Ni/TiO 2 -SiO 2 catalyst consisted of spherical particles comprising a titanosilicate phase with highly dispersed zero-valent Ni or anatase on the surface. Additionally, there was strong interaction between Ni and the TiO 2 -SiO 2 mixed oxides. Control kinetic experiments demonstrated that the tandem use of the catalysts was more effective than simultaneous operation.
Molecular weaving of chicken-wire covalent organic frameworks
Molecular weaving is the interlacing of covalently linked threads to make extended structures. Although weaving based on 3D networks has been reported, the 2D forms remain largely unexplored. Reticular chemistry uses mutually embracing tetrahedral metal complexes as crossing points, which, when linked, typically lead to 3D woven structures. Realizing 2D weaving patterns requires crossing points with an overall planar geometry. We show that polynuclear helicates composed of multiple metal-complex units, and therefore multiple turns, are well suited in this regard. By reticulating helicate units, we successfully obtained 2D weaving structures based on the familiar chicken-wire pattern.
Feedback control of an experimental electrically-heated steam methane reformer
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Comprehensive proteomics analysis of stressed human islets identifies GDF15 as a target for type 1 diabetes intervention
Type 1 diabetes results from the progressive loss of beta cells, a process propagated by pro-inflammatory cytokine signaling that disrupts the balance between the expression of pro- and anti-apoptotic proteins. To identify such proteins, we performed comprehensive proteomics of human pancreatic islets treated with interleukin-1ß and interferon-?, leading to the identification of 11,325 proteins, of which 387 were significantly regulated by treatment. We then tested the function of growth/differentiation factor 15 (GDF15), which was repressed by the cytokine treatment. We found that GDF15 translation was blocked during inflammation, while the addition of exogenous GDF15 inhibited interleukin-1ß/interferon-?-induced apoptosis of human islets and a human beta-cell line. Furthermore, administration of GDF15 significantly decreased insulitis in NOD mice. Our approach provides a unique resource for the identification of the human islet proteins regulated by cytokines and was effective in discovering a potential target for type 1 diabetes therapy.
Design of a graphical user interface for few-shot machine learning classification of electron microscopy data
The recent growth in data generation by modern electron microscopes requires rapid, scalable, and flexible approaches to image segmentation and analysis. Few-shot machine learning, which can richly classify images from a handful of user-provided examples, is a promising route to high-throughput analysis. However, current command-line implementations of such approaches can be slow and unintuitive to use, lacking the real-time feedback necessary to perform effective classification. Here we report on the development of a Python-based graphical user interface that enables end users to easily conduct and visualize the output of few-shot learning models. This interface is portable and can be hosted locally or on the web, providing the opportunity to reproducibly conduct, share, and crowd-source few-shot analyses.
A deep learning model for automatic analysis of cavities in irradiated materials
Transmission electron microscopy (TEM) is a commonly used technique in materials science for defect investigation. Quantitative analysis of defects is important for understanding the properties of a material, but manual analysis of TEM micrographs can be time-consuming and prone to error, especially when the defects have irregular shapes rather than spherical shapes. Many existing methods or deep learning models do not handle a wide range of sizes for the same object type within a single image. In this work, we present a framework that enables users to train an instance segmentation model called Mask R- CNN on any microstructure dataset, perform multi-detection on the same image at different scales, and obtain properties (e.g., size, area) of the objects based on the desired shape (e.g., circle, ellipse, rectangle). Additionally, we have developed a parallel detection module that uses multiple GPUs to increase the efficiency of the object detection process. We demonstrate the capabilities of our framework using a set of TEM images of cavities with different shapes, size distributions, and background contrasts. Finally, we show that the performance of our model in terms of density, size, and swelling of the cavities is comparable to the human average and that our model achieves the highest recall value compared to existing methods due to the use of image multi-rescaling.