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At least 235 records · Page 13

Assessment of calcium addition on the removal of U(VI) in the alkaline conditions created by NH3 gas

Remediation of uranium (U) contamination in the deep vadose zone (VZ) sediments abundant in calcite mineral is a challenging task considering the formation of highly stable and mobile uranyl complexes with carbonate and calcium in pore water composition. There is a concern that uranium contamination in the VZ can serve as a continued source for groundwater pollution, creating a risk to human health and the environment through the groundwater pathway. This requires in-situ remediation of the radionuclide-contaminated VZ to convert soluble U species to low solubility precipitates that are stable in the natural environment. Injection of reactive gasses (e.g., NH3) is a promising technology to decrease U mobility in the unsaturated zone without the addition of liquid amendments. The NH3 injection creates alkaline conditions that can alter the sediment pore water composition due to a release of elements from minerals (via desorption and dissolution) that are present in the sediment. However, it is not known how VZ pore water constituents (Si, Al3+, HCO3 -, and Ca2 +) would affect U(VI) removal/precipitation in alkaline conditions. This study quantified the role of major pore water constituents typically present in the arid and semi-arid environments of the western regions of the U.S and identified solid uranium-bearing phases that could potentially precipitate from solutions approximating pore water compositions after pH manipulations via ammonia gas injections. Triplicate samples were prepared using six Si (5, 50 100, 150, 200, and 250 mM), six HCO3 - (0, 3, 25, 50, 75, and 100 mM), and two Ca2+ (5 and 10 mM) concentrations. The concentration of aluminum and uranium was kept constant at 5mM and 0.0084 mM, respectively, in all synthetic formulations tested. Results showed that the percentage of U(VI) removal was controlled by the Si/Al molar ratios and Ca2+ concentrations. Regardless of the bicarbonate concentration tested, the percentage of U(VI) removed increased as the Si/Al ratios were increased. However, higher Ca concentrations correlated with higher U(VI) removal, ranging between 96% and 99%, at low Si/Al ratios. The SEM images of dried precipitates displayed dense amorphous regions high in silica content, where EDS elemental analysis unveiled higher U atomic percentages. The formation of uranyl silicate and carbonate minerals was also predicted by the speciation modeling. XRD analysis revealed the presence of uranyl carbonate mineral phases (andersonite, grimselite); however, uranyl silicates predicted (Naboltwoodite) were not identified experimentally, possibly due to the amorphous nature of the silica solid phases observed in our experiments.

Katsenovich, Yelena↗

Elucidating Abnormal Grain Growth in Thermomagnetic Processed Materials with Transfer Learning and Reinforcement Learning

The goal of this research program is to establish the mechanism governing local grain boundary motion, which is needed to design and process desirable microstructures for better performance, by identifying the relative contributions of grain boundary (GB) energy and mobility to grain growth. Classical models for grain growth assume that the primary mechanism for reducing the total interfacial energy is area reduction and that GB restructuring is not significant. This assumption implies that grain growth is locally driven by curvature. However, recent experimental observations using new non-destructive 3D x-ray diffraction microscopy techniques (3D-XRM) reveal that classic descriptors (i.e., curvature, number of neighbors, grain size) do not predict real grain growth. Instead, local GB motion appears to be governed by its energy relative to its neighbors such that low-energy boundaries replace those of higher energy. However, simulations that incorporate GB energy anisotropy still fail to reproduce these observations. These discrepancies suggest that the common assumption for grain growth theory must be re-examined to predict and, thus, control microstructure evolution in real polycrystals. A significant challenge to testing this assumption is due to anisotropic GB mobility. Mobility may cause abnormal grain growth or affect the final grain shapes or growth rate but its true contributions are unknown because it is difficult to measure. For example, observations in Fe have found that grains associated with high energy and high mobility boundaries tend to experience abnormal grain growth, whereas abnormal grain growth is associated with low energy and high mobility boundaries in alumina. As mobility and energy both control GB motion, it is challenging to isolate the local driving forces necessary to test the common assumption that the primary mechanism is area reduction. The novelty of this work is the use of machine learning tools to capture GB mobility and energy from 3D-XRM measurements in polycrystals to test the common assumption used in grain growth models. Machine learning can capture high-order correlations in dynamic systems like those found in the evolving GB topology. The PIs have developed a physics-regularized interpretable machine learning microstructure evolution (PRIMME) model that accurately replicates the grain growth behavior of its trained data set.

36 MATERIALS SCIENCE↗

Modeling Electric Vehicle Charging Load Using Origin-Destination Data

The accelerating adoption of electric vehicles (EVs) poses challenges to the power grid, necessitating precise representation of mobility patterns for effective infrastructure upgrades. Traditional simulation-based charging demand estimation faces limitations in generating trip chains reflective of actual travel patterns without complex network modeling. Hence, an innovative agent-based trip chain generation model is introduced to overcome these challenges. Drawing from the National Household Travel Survey (NHTS) and the NextGen NHTS origin-destination add-on data for Clarke County, Georgia, this study proposes a simulation method capturing both temporal and spatial mobility patterns without relying on extensive network topology data. The resulting trip chains predict EV charging load at the Census Block Group level, validated with a 1.03 correlation to actual trip counts, affirming their reflective accuracy. Two charging scenarios, residential-only and charging-everywhere, reveal distinct demand profiles. The charging-everywhere scenario aligns closely with the trip profile, while the residential-only scenario exhibits an afternoon peak slightly surpassing the former. This study contributes a data-driven charging demand estimation methodology, offering critical insights for grid resiliency planning amid the evolving landscape of EV adoption.

Pan, Melrose↗

Development of the Sample Fetch Rover Locomotion Subsystem

A novel system for planetary surface mobility is being designed in response to the challenging requirements of the Sample Fetch Rover (SFR) mission, part of the NASA/ESA Mars Sample Return campaign (MSR). The rover will retrieve tubes with rock and soil samples, previously acquired and cached by NASA’s Perseverance rover in depots on the Martian surface. SFR will have to acquire, transport and deliver the tubes to a lander in a tight time window. This will require significant mobility capabilities, unprecedented for Mars rovers. The highly time-constrained traverse needs, together with the strictly limited mass and volume imposed by the accommodation on the lander, have pushed the design of the SFR locomotion to seek innovative solutions. In response to that, a four-wheel drive system is being developed, integrated with a deployable pitch-averaging suspension. This will be the first time that four-wheel locomotion is used on Mars and on robotic planetary rovers in general. The system, relying on high-efficiency drive actuators designed to operate in Mars environment, shows potential for terrain and obstacle negotiation performance comparable with that of larger vehicles. The implementation also takes advantage of the superelastic Spring-Tyre technology currently being developed by NASA Glenn Research Center, which, thanks to its traction and obstacle compliance properties, will allow SFR to navigate difficult ground and achieve its mission objectives.

Rehmatullah, Faizan↗

Evaluation of Opportunistic Contact Graph Routing in Random Mobility Environments

Routing in networks where nodes move randomly is particularly challenging due their potentially unpredictable, and rapidly changing topology. Several routing algorithms have been presented in the literature to address the needs of such networks, most of them implementing variants of controlled network flooding in the hope of successful data delivery. In this note, we compare the results of previous routing algorithms with Opportunistic Contact Graph Routing (OCGR), an enhanced version of Contact Graph Routing (CGR) that is suitable for networks where contacts cannot always be scheduled ahead of time. To perform the benchmark, we simulate a network of nodes moving in a certain space according to the Random Waypoint Mobility Model, and then take measurements of bundle delivery probabilty and overhead ratio as metrics of performance and cost respectively. Through this exercise, we demonstrate that the performance of OCGR is highly dependent on the type of network under consideration (e.g. very sparse vs. densely connected) and the assumed mobility model.

Burleigh, Scott↗

Editorial overview: Omics

The great complexity of biological systems and their environment poses similarly vast challenges for accurate analytical evaluations of their identity, structure and quantity. Post genomic science, has predicted much regarding the static populations of biological systems, but a further challenge for analysis is to test the accuracy of these predictions, as well as provide a better representation of the transient nature of the molecules of life. Accurate measurements of biological systems have wide applications for biological, forensic, biotechnological and healthcare fields. Therefore, the holy grail is to find a technique which can identify and quantify biological molecules with high throughput, sensitivity and robustness, as well evaluate molecular structure(s) in order to understand how the specific molecules interact and function. While wrapping all of these characteristics into one platform may sound difficult, ion mobility spectrometry (IMS) is addressing all of these challenges. Over the last decade, the number of analytical studies utilizing IMS for the evaluation of complex biological and environmental samples has greatly increased. In most cases IMS is coupled with mass spectrometry (IM-MS), but even alone IMS provides the unique capability of rapidly assessing a molecule’s structure, which can be extremely difficult with other techniques. The robustness of the IMS measurement is bourne out by its widespread use in security, environmental and military applications. The multidimensional IM-MS measurements however have been proven to be ever more powerful, as applied to complex mixtures as they enable the evaluation of both the structure and mass of every molecular component in a sample during a single measurement, without the need for continual reference calibration.

Barran, Perdita↗

Application of Mobile Energy Storage for Enhancing Power Grid Resilience: A Review

Natural disasters can lead to large-scale power outages, affecting critical infrastructure and causing social and economic damages. These events are exacerbated by climate change, which increases their frequency and magnitude. Improving power grid resilience can help mitigate the damages caused by these events. Mobile energy storage systems, classified as truck-mounted or towable battery storage systems, have recently been considered to enhance distribution grid resilience by providing localized support to critical loads during an outage. Compared to stationary batteries and other energy storage systems, their mobility provides operational flexibility to support geographically dispersed loads across an outage area. This paper provides a comprehensive and critical review of academic literature on mobile energy storage for power system resilience enhancement. As mobile energy storage is often coupled with mobile emergency generators or electric buses, those technologies are also considered in the review. Allocation of these resources for power grid resilience enhancement requires modeling of both the transportation system constraints and the power grid operational constraints. These aspects are discussed, along with a discussion on the cost–benefit analysis of mobile energy resources. The paper concludes by presenting research gaps, associated challenges, and potential future directions to address these challenges.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Ultraviolet laser crystallized ZnO:Al films on sapphire with high Hall mobility for simultaneous enhancement of conductivity and transparency

One of the most challenging issues in transparent conductive oxides (TCOs) is to improve their conductivity without compromising transparency. High conductivity in TCO films often comes from a high carrier concentration, which is detrimental to transparency due to free carrier absorption. Here we show that UV laser crystallization (UVLC) of aluminum-doped ZnO (AZO) films prepared by pulsed laser deposition on sapphire results in much higher Hall mobility, allowing relaxation of the constraints of the conductivity/transparency trade-off. X-ray diffraction patterns and morphological characterizations show grain growth and crystallinity enhancement during UVLC, resulting in less film internal imperfections. Optoelectronic measurements show that UVLC dramatically improves the electron mobility, while the carrier concentration decreases which in turn simultaneously increases conductivity and transparency. AZO films under optimized UVLC achieve the highest electron mobility of 79 cm{sup 2}/V s at a low carrier concentration of 7.9 × 10{sup +19} cm{sup −3}. This is realized by a laser crystallization induced decrease of both grain boundary density and electron trap density at grain boundaries. The infrared (IR) to mid-IR range transmittance spectrum shows UVLC significantly enhances the AZO film transparency without compromising conductivity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

How to Extend the Capabilities of Space Systems for Long Duration Space Exploration Systems

For sustainable Exploration Missions the need exists to assemble systems-of-systems in space, on the Moon or on other planetary surfaces. To fulfill this need new and innovative system architectures must be developed to be modularized and launched with the present lift capability of existing rocket technology. To enable long duration missions with minimal redundancy and mass, system software and hardware must be reconfigurable. This will enable increased functionality and multiple use of launched assets while providing the capability to quickly overcome components failures. Additional required capability includes the ability to dynamically demate and reassemble individual system elements during a mission in order to recover from failed hardware or to adapt to changes in mission requirements. To meet the Space Exploration goals of Interoperability and Reconfigurability, many challenges must be addressed to transform the traditional static avionics architectures into architectures with dynamic capabilities. The objective of this paper is to introduce concepts associated with reconfigurable computer systems; to review the various needs and challenges associated with reconfigurable avionics space systems; to provide an operational example that illustrates the application to both the Crew Exploration Vehicle and a collection of 'Habot-like' mobile surface elements; to summarize the approaches that address key challenges to the acceptance of a Flexible, Intelligent, Modular, Affordable and Reconfigurable avionics space system.

space assembly↗

Understanding and Improving Energy Efficiency of Regional Mobility Systems Leveraging System-Level Data

Increased congestion required urban Americans to travel 6.8 billion hours more and purchase 3.1 billion gallons of fuel for a congestion cost of $\$$153 billion, according to the 2019 Urban Mobility Report. How to effectively manage the regional mobility system and improve the energy efficiency presents a big challenge to public agencies. Recent years have witnessed massive multi-jurisdictional multi-modal system-level data from various sources, which provides an unprecedented opportunity to improve the mobility system and its energy efficiency. However, implications of system-level data for mobility and energy efficiency are unclear. Those system-level data sets are siloed, spatially and temporally sparse, biased, not unified, and lacking of insights for system management. Consequently, there is a real need to acquire, fuse, mine and learn from multi-source system-level data to prepare public agencies to deal more effectively with large-scale energy efficiency modeling, management and planning. This project proposes to intensively review inexpensive, replicable and openly-accessible data from multi-modal systems, develop a data-driven system-level modeling framework enabled and validated by data, identify the energy inefficiencies of mobility systems from infrastructure, vehicles, passenger systems, and quantify the benefits of system-level strategies to improve mobility/energy efficiency. In addition, this research develops models to effectively estimate energy consumption and emissions from various types of vehicles on the roadway networks, with high granularity and high fidelity. Traditional models often heavily rely on aggregated infrastructure or vehicle/passenger data, for example, the census survey, land-use, and traffic counts of one or several classes, which may lead to research gaps considering the emerging vehicle technologies. Those models do not contain individual vehicular information. We propose an integrated data-driven method that combines multiple network modeling components, featuring the utilization of state-wide vehicle registration data. The additional vehicle registration data improve the model performance, and produce high-resolution vehicle-specific estimates of emissions and network performance metrics. Two case studies on the Pittsburgh and Philadelphia regional network show that the proposed method can efficiently and effectively estimate the emissions of a large-scale network, and provide valuable information for evaluating common management strategies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Effect of Airspace Characteristics on Urban Air Mobility Airspace Capacity

As interest in urban air mobility grows, increasingly high density traffic poses a challenge for the transition to safe, efficient, and timely operations. Hundreds of simultaneously demanded flights will need to share the same fleet, infrastructure, and constrained airspace. This paper investigates the feasibility of effectively managing high density traffic in congested urban environments by optimizing the design of airspace route structures. Demand estimations for the Dallas-Fort Worth and Los Angeles areas are used to evaluate potential improvements to airspace route design with the goal to accommodate the projected level of demand.

Urban Air Mobility↗

Semiconducting polymer blends that exhibit stable charge transport at high temperatures

Although high-temperature operation (i.e., beyond 150°C) is of great interest for many electronics applications, achieving stable carrier mobilities for organic semiconductors at elevated temperatures is fundamentally challenging. Here, we report a general strategy to make thermally stable high-temperature semiconducting polymer blends, composed of interpenetrating semicrystalline conjugated polymers and high glass-transition temperature insulating matrices. When properly engineered, such polymer blends display a temperature-insensitive charge transport behavior with hole mobility exceeding 2.0 cm 2 /V·s across a wide temperature range from room temperature up to 220°C in thin-film transistors.

30 DIRECT ENERGY CONVERSION↗

Effect of Airspace Characteristics on Urban Air Mobility Airspace Capacity

As interest in urban air mobility grows, increasingly high density traffic poses a challenge for the transition to safe, efficient, and timely operations. Hundreds of simultaneously demanded flights will need to share the same fleet, infrastructure, and constrained airspace. This paper investigates the feasibility of effectively managing high density traffic in congested urban environments by optimizing the design of airspace route structures. Demand estimations for the Dallas-Fort Worth and Los Angeles areas are used to evaluate potential improvements to airspace route design with the goal to accommodate the projected level of demand.

Urban Air Mobility↗

2024 University of Puerto Rico at Mayagüez Civic Innovation Challenge Study

# 2024 University of Puerto Rico at Mayagüez Civic Innovation Challenge Study The 2024 University of Puerto Rico at Mayagüez Civic Innovation Challenge (CIVIC) Study provided insight into the travel patterns and associated energy consumption of participants. Study results helped researchers identify opportunities for the development of shared mobility strategies—such as collaborative ride-sharing programs—that could address the mobility needs of rural communities in Puerto Rico. The Civic Innovation Challenge is a multiagency, federal government research and action competition that funds ready-to-implement, research-based pilot projects that have the potential for scalable, sustainable, and transferable impact on community-identified priorities. ## Data Collection Agency The University of Puerto Rico at Mayagüez conducted the study. ## Survey Methodology The study was conducted in Spanish. Data collection was enabled via the open-source [NREL OpenPATH platform](https://www.nrel.gov/transportation/openpath). The resulting dataset consists of partially automated travel diaries—combining sensed and surveyed data reflecting patterns of multimodal, end-to-end, individual human mobility—as well as demographic and socioeconomic information from the 31 participants. ## Survey Records, Data, and Documentation Survey records include 31 participants. The total number of trips was 1,373 and the total non-air-miles traveled was approximately 8,260.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

2024 University of Puerto Rico at Mayagüez Civic Innovation Challenge Study

# 2024 University of Puerto Rico at Mayagüez Civic Innovation Challenge Study The 2024 University of Puerto Rico at Mayagüez Civic Innovation Challenge (CIVIC) Study provided insight into the travel patterns and associated energy consumption of participants. Study results helped researchers identify opportunities for the development of shared mobility strategies—such as collaborative ride-sharing programs—that could address the mobility needs of rural communities in Puerto Rico. The Civic Innovation Challenge is a multiagency, federal government research and action competition that funds ready-to-implement, research-based pilot projects that have the potential for scalable, sustainable, and transferable impact on community-identified priorities. ## Data Collection Agency The University of Puerto Rico at Mayagüez conducted the study. ## Survey Methodology The study was conducted in Spanish. Data collection was enabled via the open-source [NREL OpenPATH platform](https://www.nrel.gov/transportation/openpath). The resulting dataset consists of partially automated travel diaries—combining sensed and surveyed data reflecting patterns of multimodal, end-to-end, individual human mobility—as well as demographic and socioeconomic information from the 31 participants. ## Survey Records, Data, and Documentation Survey records include 31 participants. The total number of trips was 1,373 and the total non-air-miles traveled was approximately 8,260.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

2024 University of Puerto Rico at Mayagüez Civic Innovation Challenge Study

# 2024 University of Puerto Rico at Mayagüez Civic Innovation Challenge Study The 2024 University of Puerto Rico at Mayagüez Civic Innovation Challenge (CIVIC) Study provided insight into the travel patterns and associated energy consumption of participants. Study results helped researchers identify opportunities for the development of shared mobility strategies—such as collaborative ride-sharing programs—that could address the mobility needs of rural communities in Puerto Rico. The Civic Innovation Challenge is a multiagency, federal government research and action competition that funds ready-to-implement, research-based pilot projects that have the potential for scalable, sustainable, and transferable impact on community-identified priorities. ## Data Collection Agency The University of Puerto Rico at Mayagüez conducted the study. ## Survey Methodology The study was conducted in Spanish. Data collection was enabled via the open-source [NREL OpenPATH platform](https://www.nrel.gov/transportation/openpath). The resulting dataset consists of partially automated travel diaries—combining sensed and surveyed data reflecting patterns of multimodal, end-to-end, individual human mobility—as well as demographic and socioeconomic information from the 31 participants. ## Survey Records, Data, and Documentation Survey records include 31 participants. The total number of trips was 1,373 and the total non-air-miles traveled was approximately 8,260.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

2024 University of Puerto Rico at Mayagüez Civic Innovation Challenge Study

# 2024 University of Puerto Rico at Mayagüez Civic Innovation Challenge Study The 2024 University of Puerto Rico at Mayagüez Civic Innovation Challenge (CIVIC) Study provided insight into the travel patterns and associated energy consumption of participants. Study results helped researchers identify opportunities for the development of shared mobility strategies—such as collaborative ride-sharing programs—that could address the mobility needs of rural communities in Puerto Rico. The Civic Innovation Challenge is a multiagency, federal government research and action competition that funds ready-to-implement, research-based pilot projects that have the potential for scalable, sustainable, and transferable impact on community-identified priorities. ## Data Collection Agency The University of Puerto Rico at Mayagüez conducted the study. ## Survey Methodology The study was conducted in Spanish. Data collection was enabled via the open-source [NREL OpenPATH platform](https://www.nrel.gov/transportation/openpath). The resulting dataset consists of partially automated travel diaries—combining sensed and surveyed data reflecting patterns of multimodal, end-to-end, individual human mobility—as well as demographic and socioeconomic information from the 31 participants. ## Survey Records, Data, and Documentation Survey records include 31 participants. The total number of trips was 1,373 and the total non-air-miles traveled was approximately 8,260.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

2024 University of Puerto Rico at Mayagüez Civic Innovation Challenge Study

# 2024 University of Puerto Rico at Mayagüez Civic Innovation Challenge Study The 2024 University of Puerto Rico at Mayagüez Civic Innovation Challenge (CIVIC) Study provided insight into the travel patterns and associated energy consumption of participants. Study results helped researchers identify opportunities for the development of shared mobility strategies—such as collaborative ride-sharing programs—that could address the mobility needs of rural communities in Puerto Rico. The Civic Innovation Challenge is a multiagency, federal government research and action competition that funds ready-to-implement, research-based pilot projects that have the potential for scalable, sustainable, and transferable impact on community-identified priorities. ## Data Collection Agency The University of Puerto Rico at Mayagüez conducted the study. ## Survey Methodology The study was conducted in Spanish. Data collection was enabled via the open-source [NREL OpenPATH platform](https://www.nrel.gov/transportation/openpath). The resulting dataset consists of partially automated travel diaries—combining sensed and surveyed data reflecting patterns of multimodal, end-to-end, individual human mobility—as well as demographic and socioeconomic information from the 31 participants. ## Survey Records, Data, and Documentation Survey records include 31 participants. The total number of trips was 1,373 and the total non-air-miles traveled was approximately 8,260.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗