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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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pH-Mediated Colorimetric and Luminescent Sensing of Aqueous Nitrate Anions by a Platinum(II) Luminophore@Mesoporous Silica Composite

Increased levels of nitrate (NO 3 – ) in the environment can be detrimental to human health. Herein, we report a robust, cost-effective, and scalable, hybrid material-based colorimetric/luminescent sensor technology for rapid, selective, sensitive, and interference-free in situ NO 3 – detection. These hybrid materials are based on a square-planar platinum(II) salt [Pt(tpy)Cl]PF6 (tpy = 2,2';6',2''-terpyridine) supported on mesoporous silica. The platinum salt undergoes a vivid change in color and luminescence upon exposure to aqueous NO 3 – anions at pH ≤ 0 caused by substitution of the PF6– anions by aqueous NO 3 – . This change in photophysics of the platinum salt is induced by a rearrangement of its crystal lattice that leads to an extended Pt···Pt···Pt interaction, along with a concomitant change in its electronic structure. Furthermore, incorporating the material into mesoporous silica enhances the surface area and increases the detection sensitivity. A NO 3 – detection limit of 0.05 mM (3.1 ppm) is achieved, which is sufficiently lower than the ambient water quality limit of 0.16 mM (10 ppm) set by the United States Environmental Protection Agency. The colorimetric/luminescence of the hybrid material is highly selective to aqueous NO 3 – anions in the presence of other interfering anions, suggesting that this material is a promising candidate for the rapid NO 3 – detection and quantification in practical samples without separation, concentration, or other pretreatment steps.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Interference Moral Hazard in Large Multihop Networks

Cooperation between network nodes is critical for supporting services in ad hoc networks. Cooperation, however, is an idealized assumption that may not always be present. This assumption can fail because of moral hazard, a scenario in part caused by misaligned incentives between the requesting node and supporting node. In this paper, we characterize a moral hazard that perversely incentivizes nodes to increase their routing payments by transmitting interference into the multi-hop network. We refer to this as the interference moral hazard (IMH) problem which is inherent to strategyproof mechanisms with low overpayments. We investigate IMH as a non-cooperative game played by network nodes on a random graph. For large networks, we show that IMH can be solved in the network design space. Finally, we provide sufficient conditions on the network distribution that guarantee an equilibrium path with interference-free play. This is achieved by 1) lower-bounding the number of nodes and 2) bounding the network density slightly above the 2-connectedness threshold and below a proposed upper-bound. Simulations suggest that density plays a fundamental role in IMH.

42 ENGINEERING↗

AviSense: A Real-time System for Detection, Classification, and Analysis of Aviation Signals

Wireless systems are an integral part of aviation. Apart from their apparent use in air-to-ground communication, wireless systems play a crucial role in avionic functions including navigation and landing. An interference-free wireless environment is therefore critical for the uninterrupted operation and safety of an aircraft. Hence, there is an urgency for airport facilities to acquire the capability to continuously monitor aviation frequency bands for real-time detection of interference and anomalies. To meet this critical need, we design and build AviSense, an SDR-based real-time, versatile system for monitoring aviation bands. AviSense detects and characterizes signal activities to enable practical and effective anomaly detection. We identify and tackle the challenges posed by a diverse set of critical aviation bands and technologies. We evaluate our methodology with real-world aviation signal measurements and two custom datasets of anomalous signals. We find that our signal classification capability achieves a true positive rate of ~99%, with few exceptions, and a false positive rate of less than 4%. We also demonstrate that AviSense can effectively distinguish between different types of anomalies. We build and evaluate a prototype implementation of AviSense that supports distributed monitoring.

42 ENGINEERING↗

TMTpro Complementary Ion Quantification Increases Plexing and Sensitivity for Accurate Multiplexed Proteomics at the MS2 Level

Multiplexed proteomics is a powerful tool to assay cell states in health and disease, but accurate quantification of relative protein changes is impaired by interference from co-isolated peptides. Most widely, this issue is alleviated by MS3-based quantification, reducing sensitivity and requiring specialized instrumentation. An alternative approach is quantification by complementary ions, which allows accurate and precise multiplexed quantification at the MS2 level and is compatible with the most widely distributed instruments. However, complementary ions of the popular TMT tag form inefficiently and plexing is limited to five channels. In this work, we evaluate and optimize complementary ion quantification for the recently released TMTPro tag, which increases plexing capacity to 8 channels (TMTProC). We find that the beneficial fragmentation properties increase quantification signal five-fold compared to TMT. This increased sensitivity results in ~50% more proteins quantified compared to TMTPro-MS3 and even slightly outperforms TMTPro-MS2. Furthermore, TMTProC quantification is more accurate than TMTPro-MS2 and even superior to TMTPro-MS3. To demonstrate the power of TMTProC, we analyzed a human and yeast interference sample and were able to quantify 13,290 proteins in 24 fractions. Thus, TMTProC advances multiplexed proteomics data quality and widens access to accurate multiplexed proteomics beyond laboratories with MS3-capable instrumentation.

59 BASIC BIOLOGICAL SCIENCES↗