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At least 541 records · Page 30

Enhancing the Electrocatalysis of LiNi 0.5 Co 0.2 Mn 0.3 O 2 by Introducing Lithium Deficiency for Oxygen Evolution Reaction

LiNi 0.5 Co 0.2 Mn 0.3 O 2 (NCM523), as a cathode material for rechargeable lithium-ion batteries, has attracted considerable attention and been successfully commercialized for decades. NCM is also a promising electrocatalyst for the oxygen evolution reaction (OER), and the catalytic activity is highly correlated to its structure. In this paper, we successfully obtain NCM523 with three different structures: spinel NCM synthesized at low temperature (LT-NCM), disordered NCM (DO-NCM) with lithium deficiency obtained at high temperature, and layered hexagonal NCM at high temperature (HT-NCM). By introducing lithium deficiency to tune the valence state of transition metals in NCM from Ni 2+ to Ni 3+ , DO-NCM exhibits the best catalytic activity with the lowest onset potential (~1.48 V) and Tafel slope (~85.6 mV dec -1 ), whereas HT-NCM exhibits the worst catalytic activity with the highest onset potential (~1.63 V) and Tafel slope (~241.8 mV dec -1 ).

36 MATERIALS SCIENCE↗

Triphenylphosphine Oxide-Derived Anolyte for Application in Nonaqueous Redox Flow Battery

Recent advances in redox flow batteries have made them a viable option for grid-scale energy storage, however they exhibit low energy density. One way to boost energy density is by increasing the cell potential using a nonaqueous system. Molecular engineering has proven to be an effective strategy to develop redox-active compounds with extreme potentials but these are usually challenged by resource sustainability of the newly developed redox materials. Here, we investigate the utility of phosphine oxides as anolytes with extremely negative potentials. Specifically, we found that cyclic triphenylphosphine oxide (CPO), has a highly negative potential (–2.4 V vs Fc/Fc + ). Importantly, CPO is synthesized from triphenylphosphine oxide, a common industrial chemical waste with no commercial value. Structural and electrochemical characterization of the reduced radical anion showed that enhanced stability is due to cyclization or extended pi-conjugation. Importantly, mechanistic investigation into the decomposition of CPO under various solvents and electrochemical conditions allowed us to utilize an acetonitrile/DMF binary solvent system to enable a long-lived anolyte which exhibited no fade over 350 cycles. In conclusion, this work led to the development of a waste-derived cyclic phosphine oxide that exhibits excellent cycling stability making it an ideal anolyte toward the development of energy-dense RFBs.

25 ENERGY STORAGE↗

Identifying Hot Spots and Hot Moments of Metabolic Activity in Salt Marsh Sediments through BONCAT-FISH Microscale Mapping (Final Technical Report)

Understanding the biogeography and timing of microbial metabolic activity is a key priority for microbial ecologists. With such knowledge, the cumulative biogeochemical contributions of microbial communities become more predictable, and our ability to both understand the effects of environmental change on microbial activity and build synthetic communities with desired functions will increase substantially. In this project, we advanced this broad, ambitious goal in two substantial ways: we developed a multiplexed Fluorescence In Situ Hybridization (FISH) approach that links microbial identity with metabolic function, and we established a novel Bio-Orthogonal Non-Canonical Amino acid Tagging (BONCAT) technique that can resolve the timing of anabolic activity, providing new resolution of when microbial constituents are growing. We deployed both of these techniques in multiple environmental settings to demonstrate their versatility. At the Little Sippewissett Salt Marsh, we combined a novel dual-BONCAT technique with fluorescence activated cell sorting to determine which population of cells was metabolically active during the day and which was active during the night. We found that Methylobacterium was active during daylight hours, potentially feeding on carbon-rich molecules released from plant roots. Sulfur-cycling microbes dominate the population active during the dark night-time hours. Overall, the work conducted under the auspices of this project developed two promising new techniques for identifying the “hot spots” and “hot moments” of microbial activity in complex communities with taxonomic and functional resolution. We focused largely on a salt marsh sediment context, but are confident that microbial ecologists seeking to understand the microbial role in biogeochemical cycles in a wide range of settings will find our newly developed techniques useful in future work.

54 ENVIRONMENTAL SCIENCES↗

Analyzing Federal Agency Earth Observation Needs: NASA’s 2022 Satellite Needs Working Group Assessment

Every two years, the National Aeronautics and Space Administration (NASA) leads an assessment of Federal civilian agency Earth observation needs submitted through the Satellite Needs Working Group (SNWG) survey. Nearly 30 agencies participated in the 2022 SNWG survey, submitting 115 high-priority satellite data needs that span Earth Science and represent a wide variety of potential applications for Earth observation data. Analysis of multiple SNWG survey cycles reveals trends in agency needs toward more frequent, higher resolution data that can inform agency decision-making. NASA and partners at the National Oceanic and Atmospheric Administration (NOAA) and U.S. Geological Survey (USGS) evaluated the agency surveys during an eight-month assessment period. Assessment teams comprised of subject matter experts, technology specialists, and agency managers conducted an in-depth interview with each submitting agency to fully understand the need and discuss relevant current and upcoming satellite missions. The teams then proposed over 100 potential solutions, or new activities that NASA, NOAA, and/or USGS could undertake to help meet agency needs. A few cross-cutting potential solutions that are projected to be most valuable to SNWG agencies are under consideration for implementation by NASA in the coming years.

Katrina Virts↗

Subjective Assessment of Initial and Mid-Term UAM Operations and the Impact on Air Traffic Controllers' Workload

The emergence of Urban Air Mobility (UAM) marks a new era of aviation that will be characterized by a shift in transportation dynamics marked by safe, efficient, and sustainable air travel within urban areas. Although UAM will provide significant advantages, increased air travel demand has the potential to impact air traffic controllers (ATCo) workload. Therefore, industry, government, and academia in the UAM ecosystem are actively working to overcome potential implementation challenges that include airspace integration and air traffic management. As part of this effort, researchers from the National Aeronautics and Space Administration (NASA) are studying the challenges associated with UAM operations’ interactions with air traffic control (ATC). The present research paper presents an analysis of subjective assessments to determine the usability and acceptability of airspace procedures under two different operating conditions – Initial and Mid-Term – and two different levels of UAM traffic. The completion of these investigations will be a steppingstone in supporting the successful implementation of UAM operations into the National Airspace System.

Urban Air Mobility, Air Traffic Control, Workload↗

Subjective Assessment of Initial and Mid-Term UAM Operations and the Impact on Air Traffic Controllers' Workload

The emergence of Urban Air Mobility (UAM) marks a new era of aviation that will be characterized by a shift in transportation dynamics marked by safe, efficient, and sustainable air travel within urban areas. Although UAM will provide significant advantages, increased air travel demand has the potential to impact air traffic controllers (ATCo) workload. Therefore, industry, government, and academia in the UAM ecosystem are actively working to overcome potential implementation challenges that include airspace integration and air traffic management. As part of this effort, researchers from the National Aeronautics and Space Administration (NASA) are studying the challenges associated with UAM operations’ interactions with air traffic control (ATC). The present research paper presents an analysis of subjective assessments to determine the usability and acceptability of airspace procedures under two different operating conditions – Initial and Mid-Term – and two different levels of UAM traffic. The completion of these investigations will be a steppingstone in supporting the successful implementation of UAM operations into the National Airspace System.

Urban Air Mobility↗

Single-Atomic Site Catalyst Enhanced Lateral Flow Immunoassay for Point-of-Care Detection of Herbicide

Point-of-care (POC) detection of herbicides is of great importance due to their impact on the environment and potential risks to human health. Here, we design a single-atomic site catalyst (SASC) with excellent peroxidase-like (POD-like) catalytic activity, which enhances the detection performance of corresponding lateral flow immunoassay (LFIA). The iron single-atomic site catalyst (Fe-SASC) is synthesized from hemin-doped ZIF-8, creating active sites that mimic the Fe active center coordination environment of natural enzyme and their functions. Due to its atomically dispersed iron active sites that result in maximum utilization of active metal atoms, the Fe-SASC exhibits superior POD-like activity, which has great potential to replace its natural counterparts. Also, the catalytic mechanism of Fe-SASC is systematically investigated. Utilizing its outstanding catalytic activity, the Fe-SASC is used as label to construct LFIA (Fe-SASC-LFIA) for herbicide detection. The 2,4-dichlorophenoxyacetic acid (2,4-D) is selected as a target here, since it is a commonly used herbicide as well as a biomarker for herbicide exposure evaluation. A linear detection range of 1-250 ng/mL with a low limit of detection (LOD) of 0.82 ng/mL has been achieved. Meanwhile, excellent specificity and selectivity towards 2,4-D have been obtained. The outstanding detection performance of the Fe-SASC-LFIA has also been demonstrated in the detection of human urine samples, indicating the practicability of this POC detection platform for analyzing the 2,4-D exposure level of a person. We believe this proposed Fe-SASC-LFIA has potential as a portable, rapid, and high-sensitive POC detection strategy for pesticide exposure evaluation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Propane Activation on Pt Electrodes at Room Temperature: Quantification of Adsorbate Identity and Coverage

Abstract C−H bond activation is the first step in manufacturing chemical products from readily available light alkane feedstock and typically proceeds via carbon‐intensive thermal processes. The ongoing emphasis on decarbonization via electrification motivates low‐temperature electrochemical alternatives that could lead to sustainable chemicals production. Platinum (Pt) electrocatalysts have shown activity towards reacting alkanes; however, little is known about propane electrocatalytic activation and conditions suitable for enabling selective oxidation to valuable products. Herein, we utilize a combination of electrochemical mass spectrometry (ECMS) and density functional theory (DFT) calculations to elucidate the potential dependence of propane activation on Pt electrocatalysts. Results show a strong dependence of adsorption on the applied potential in room‐temperature aqueous acidic electrolyte, with a maximum coverage of propane‐derived adsorbates at 0.30 V vs RHE. Using charge deconvolution and deuterated experiments, the mechanism of adsorption was elucidated, and C 3 H 2 * was determined as the average dehydrogenated propane‐derived adsorbate species. DFT calculations further corroborate these results, showing that the formation of deeply dehydrogenated species is energetically accessible at room temperature. The combined theoretical and experimental findings yield insights for selective activation of paraffinic C−H bonds at room temperature, aqueous conditions—a critical step towards decarbonized chemical manufacturing.

Chemistry↗

Feasibility of simultaneous operation of passive remote microwave sensors and active services occupying adjacent frequency bands

To ensure proper sensor operations, it is necessary to understand the situation of potential interference to sensors due to active equipment sharing common frequency bands as well as equipment occupying adjacent bands. The feasibility of sharing common frequency bands between passive sensors and other active services was analyzed. Potential interference to sensors due to equipment in bands adjacent to sensor frequency bands is examined and criteria to avoid interference is developed.

Sue, M. K.↗

Investigating Deposition Sequence During Synthesis of Pd/Al2O3 Catalysts Modified with Organic Monolayers

Modification of supported metal catalysts with self-assembled monolayers (SAMs) has been shown to improve selectivity and turnover frequencies (TOFs) for many catalytic reactions. However, these benefits are often accompanied by a decrease in overall mass activity due to partial blocking of active sites by the monolayers. Therefore, a potential method for increasing site accessibility is to deposit the active metal (e.g., Pd) after deposition of a SAM modifier on the support material. In this work, Pd/Al2O3 catalysts were synthesized using both a conventional, "metal-first" sequence in which the phosphonic acid (PA) SAM was deposited on Pd/Al2O3 and a "SAM-first" technique in which the ligands were deposited onto the support prior to deposition of the metal. Although metal-first catalysts showed a significant increase in TOF during benzyl alcohol HDO, they exhibited only a modest increase in overall mass activity due to a decrease in the number of active sites. Meanwhile, SAM-first catalysts showed similar improvements in TOF and toluene selectivity but exhibited significantly improved HDO rates compared to metal-first catalysts. The rate increase was attributed to reduced site blocking as evidenced by CO chemisorption measurements. Additionally, analysis of catalysts having high Pd loadings using transmission electron microscopy (TEM) showed that SAM-first catalysts generally resulted in lower average particle sizes than traditionally modified and unmodified catalysts, suggesting that precoating the support surface with PAs changes the way that Pd is deposited during incipient wetness, leading here to improved activity.

catalytic reactions↗

Does Aspartic Acid Racemization Constrain the Depth Limit of the Subsurface Biosphere?

Previous studies of the subsurface biosphere have deduced average cellular doubling times of hundreds to thousands of years based upon geochemical models. We have directly constrained the in situ average cellular protein turnover or doubling times for metabolically active micro-organisms based on cellular amino acid abundances, D/L values of cellular aspartic acid, and the in vivo aspartic acid racemization rate. Application of this method to planktonic microbial communities collected from deep fractures in South Africa yielded maximum cellular amino acid turnover times of approximately 89 years for 1 km depth and 27 C and 1-2 years for 3 km depth and 54 C. The latter turnover times are much shorter than previously estimated cellular turnover times based upon geochemical arguments. The aspartic acid racemization rate at higher temperatures yields cellular protein doubling times that are consistent with the survival times of hyperthermophilic strains and predicts that at temperatures of 85 C, cells must replace proteins every couple of days to maintain enzymatic activity. Such a high maintenance requirement may be the principal limit on the abundance of living micro-organisms in the deep, hot subsurface biosphere, as well as a potential limit on their activity. The measurement of the D/L of aspartic acid in biological samples is a potentially powerful tool for deep, fractured continental and oceanic crustal settings where geochemical models of carbon turnover times are poorly constrained. Experimental observations on the racemization rates of aspartic acid in living thermophiles and hyperthermophiles could test this hypothesis. The development of corrections for cell wall peptides and spores will be required, however, to improve the accuracy of these estimates for environmental samples.

cellular↗

Speed of CMEs and the Magnetic Non-Potentiality of Their Source ARs

Most fast coronal mass ejections (CMEs) originate from solar active regions (ARs). Non-potentiality of ARs is expected to determine the speed and size of CMEs in the outer corona. Several other unexplored parameters might be important as well. To find out the correlation between the initial speed of CMEs and the non-potentiality of source ARs, we associated over a hundred of CMEs with source ARs via their co-produced flares. The speed of the CMEs are collected from the SOHO LASCO CME catalog. We have used vector magnetograms obtained mainly with HMI/SDO, also with Hinode (SOT/SP) when available within an hour of a CME occurrence, to evaluate various magnetic non-potentiality parameters, e.g. magnetic free-energy proxies, computed magnetic free energy, twist, shear angle, signed shear angle etc. We have also included several other parameters e.g. total unsigned flux, net current, magnetic area of ARs, area of sunspots, to investigate their correlation, if any, with the initial speeds of CMEs. Our preliminary results show that the ARs with larger non-potentiality and area mostly produce fast CMEs but they can also produce slower ones. The ARs with lesser non-potentiality and area generally produce only slower CMEs, however, there are a few exceptions. The total unsigned flux correlate with the non-potentiality parameters and area of ARs but some ARs with large unsigned flux are also found to be least non-potential. A more detailed analysis is underway.

Tiwari, Sanjiv K.↗

Analysis and visualization of single-trial event-related potentials

In this study, a linear decomposition technique, independent component analysis (ICA), is applied to single-trial multichannel EEG data from event-related potential (ERP) experiments. Spatial filters derived by ICA blindly separate the input data into a sum of temporally independent and spatially fixed components arising from distinct or overlapping brain or extra-brain sources. Both the data and their decomposition are displayed using a new visualization tool, the "ERP image," that can clearly characterize single-trial variations in the amplitudes and latencies of evoked responses, particularly when sorted by a relevant behavioral or physiological variable. These tools were used to analyze data from a visual selective attention experiment on 28 control subjects plus 22 neurological patients whose EEG records were heavily contaminated with blink and other eye-movement artifacts. Results show that ICA can separate artifactual, stimulus-locked, response-locked, and non-event-related background EEG activities into separate components, a taxonomy not obtained from conventional signal averaging approaches. This method allows: (1) removal of pervasive artifacts of all types from single-trial EEG records, (2) identification and segregation of stimulus- and response-locked EEG components, (3) examination of differences in single-trial responses, and (4) separation of temporally distinct but spatially overlapping EEG oscillatory activities with distinct relationships to task events. The proposed methods also allow the interaction between ERPs and the ongoing EEG to be investigated directly. We studied the between-subject component stability of ICA decomposition of single-trial EEG epochs by clustering components with similar scalp maps and activation power spectra. Components accounting for blinks, eye movements, temporal muscle activity, event-related potentials, and event-modulated alpha activities were largely replicated across subjects. Applying ICA and ERP image visualization to the analysis of sets of single trials from event-related EEG (or MEG) experiments can increase the information available from ERP (or ERF) data. Copyright 2001 Wiley-Liss, Inc.

Non-NASA Center↗

Active Chevrons for Jet Noise Reduction

Jet noise is often a dominant component of aircraft noise, particularly at takeoff. To meet the stringent noise regulations, the aircraft industry is in a pressing need of advanced noise reduction concepts. In the present study, the potential of piezoelectrically-activated chevrons for jet noise reduction was experimentally investigated. The perturbations near the nozzle exit caused by piezoelectrically-activated chevrons could be used to modify the growth rate of the mixing layer and thereby potentially reduce jet noise. These perturbations are believed to increase the production of small-scale disturbances at the expense of large-scale turbulent structures. These large-scale turbulent structures are responsible for the dominant portion of the jet mixing noise, particularly low-frequency noise. Therefore, by exciting the static chevron geometry through piezoelectric actuators, an additional acoustic benefit could possibly be achieved. To aid in the initial implementation of this concept, several flat-faced faceted nozzles (four, six, and eight facets) were investigated. Among the faceted nozzles, it was found that the eight-faceted nozzle behaves very similarly to the round nozzle. Furthermore, among the faceted nozzles with static chevrons, the four-faceted nozzle with static chevrons was found to be most effective in terms of jet noise reduction. The piezoelectrically-activated chevrons reduced jet noise up to 2 dB compared to the same nozzle geometry without excitation. This benefit was observed over a wide range of excitation frequencies by applying very low voltages to the piezoelectric actuators.

Depuru-Mohan, N. K.↗

Analyzing Risks of Virtual Private Network Connections

The use of Splunk for analyzing VPN logs is an effective approach for identifying vulnerabilities in network endpoints. Splunk, a powerful platform for searching, monitoring, and analyzing machine-generated data, enables organizations to aggregate VPN logs in real-time, providing insights into network activity, user behavior, and potential security risks. By indexing VPN traffic and authentication logs, security teams can track abnormal patterns such as multiple failed login attempts, unusual IP addresses, or unexpected changes in bandwidth usage, all of which could indicate potential vulnerabilities or breaches. With Splunk’s advanced search and reporting capabilities, users can create custom dashboards and alerts to detect suspicious activities. Automated searches can flag endpoints exhibiting unusual behavior, while correlation analysis can identify links between compromised devices and broader network vulnerabilities. In particular, Splunk's machine learning capabilities can be leveraged to predict and prevent threats by identifying trends that might otherwise be missed in traditional log analysis. This proactive approach to monitoring VPN logs allows for the early detection of security weaknesses, enabling rapid response and minimizing potential damage to network integrity. By enhancing endpoint visibility, Splunk plays a crucial role in securing remote connections and safeguarding sensitive information. Additionally, Splunk’s automation and alerting features allow teams to create custom workflows that notify them of vulnerable or misconfigured endpoints identified through Shodan. This synergy between Splunk’s log analysis and Shodan’s device intelligence enhances an organization’s ability to proactively identify and mitigate security risks, improving the overall resilience of their VPN infrastructure.

97 MATHEMATICS AND COMPUTING↗

Iron redox behavior and oxygen reduction activity of Fe-N-C electrocatalysts in different electrolytes

The iron redox behavior and oxygen reduction reaction (ORR) activity of Fe-N-C ORR electrocatalysts synthesized by a variety of techniques were investigated as a function of the identity of the electrolyte anion (bisulfate/sulfate or perchlorate) at a constant pH. In situ X-ray absorption spectroscopy data support the assignment of the redox peaks in the voltammograms to the Fe 3+ /Fe 2+ redox couple. It was found that for a given Fe-N-C catalyst, there is a correlation between the Fe redox couple peak potential and the ORR activity in perchloric acid electrolyte, but not in sulfuric acid electrolyte. While a higher Fe redox couple potential (≥ 110 mV higher) was observed in perchloric acid electrolyte, a higher ORR activity was obtained in sulfuric acid electrolyte. Here, the higher ORR activity observed in sulfuric acid than perchloric acid was correlated with the higher peak current and larger faradaic charge for the Fe redox couple. A study of the Fe redox behavior using a cavity microelectrode, eliminating the impact of ionomer, showed that the interaction of H 2 SO 4 with Fe-N-C is stronger than that of HClO 4 and that Fe redox in both electrolytes is a reversible surface electrochemical reaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Fox Trails

1. This software utilizes python pandas to pull data from P6 databases or XER files. The software transforms the datasets into multiple main tables by joining, filtering, iteratively flattening hierarchical structured data, and pivoting datasets to give simple flat output tables. The activity table includes all of the information related to an activity including activity codes, global, EPS, and project codes, UDFs, and WBS information as separate columns. This includes the code id, code value and sequence number for all levels in hierarchical codes. The resource table is similar to the activity table and includes all of the information related to resources on activities including UPFs and resource codes. The resource time phased table takes the resource information and time phases it for the budget, forecast, late, and actual dates/units/costs that closely matches P6's user interface's values as it implements the resource curve and calendars. The wbs table contains the WBS structure broken out by levels and includes UDFs, codes, and notebook topics. The final P6 data table is the relationships table which simply contains the relationships. 2. When a user updates the tool with data (via giving it P6 project names with database username/password information or XER files) the system creates the data in #1, then creates a networkx graph with the activity data imbedded in the node data and the relationships added as edges. Each edge also has it's float calculated (working time distance between the predecessor and successor) and attached to the edge. Activities are also tagged as a potential start of a path based on their constraints, constraint dates, remaining start date, and activity status. When a user enters an activity ID into the UI, it runs a shortest path calculation on the network graph between each node tagged as potential start to the entered activity id based on the float tagged on the edge. Each path returned by the algorithm contains all of the nodes on the path in order, as well as the total float of the edges that make the path. This data is then collected and returned to the user in the form of a gantt chart with groupings for each path that includes the total float for each group. 3. Similar to 2, if the user passes through a reference dataset each activity set in the path is checked to see if it had a path in the reference dataset, if that path was the primary path between the start and end activities, and what has changed regarding logic and durations. These changes are color coded and summarized before sent to the user to be displayed by the UI for simple discovery. 4. Utilizing the data from #1, the user can submit desired grouping code(s) and filters to the system. The system will then pull the activities, resources, and relationships and create a gantt chart based on the groupings sent and filtered based on the filters sent. 5. The system will produce a gantt chart in a similar method to #4, but allows interactivity with the data. As the user interacts with the gantt chart, the software captures the changes and stores it with the user making the change so that project controls and implement those changes in P6.

Fox, Ben↗

Human factors process failure modes and effects analysis (HF PFMEA) software tool

Methods, computer-readable media, and systems for automatically performing Human Factors Process Failure Modes and Effects Analysis for a process are provided. At least one task involved in a process is identified, where the task includes at least one human activity. The human activity is described using at least one verb. A human error potentially resulting from the human activity is automatically identified, the human error is related to the verb used in describing the task. A likelihood of occurrence, detection, and correction of the human error is identified. The severity of the effect of the human error is identified. The likelihood of occurrence, and the severity of the risk of potential harm is identified. The risk of potential harm is compared with a risk threshold to identify the appropriateness of corrective measures.

Chandler, Faith T.↗