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DOE OSTI2024

Electron mobility enhancement by electric field engineering of AlN/GaN/AlN quantum-well HEMTs on single-crystal AlN substrates

To enhance the electron mobility in quantum-well high-electron-mobility transistors (QW HEMTs), we investigate the transport properties in AlN/GaN/AlN heterostructures on Al-polar single-crystal AlN substrates. Theoretical modeling combined with experiment shows that interface roughness scattering due to high electric field in the quantum well limits mobility. Increasing the width of the quantum well to its relaxed form reduces the internal electric field and scattering, resulting in a binary QW HEMT with a high two-dimensional electron gas (2DEG) density of 3.68×1013 cm–2, a mobility of 823 cm2/Vs, and a record-low room temperature (RT) sheet resistance of 206 Ω/□. Further reduction of the quantum well electric field yields a 2DEG density of 2.53×1013 cm–2 and RT mobility > 1000 cm2/V s. These findings will enable future developments in high-voltage and high-power microwave applications on the ultrawide bandgap AlN substrate platform.

Physics↗

DOE OSTI2017

Negative differential mobility and trapping in active matter systems

Using simulations, we explore the average velocity as a function of applied drift force for active matter particles moving through a random obstacle array. We find that for low drift force, there is an initial flow regime where the mobility increases linearly with drive, while for higher drift forces a regime of negative differential mobility appears in which the velocity decreases with increasing drive due to the trapping of active particles behind obstacles. A fully clogged regime exists at very high drift forces when all the particles are permanently trapped behind obstacles. We discover for increasing activity that the overall mobility is nonmonotonic, with an enhancement of the mobility for small levels of activity and a decrease in mobility for large activity levels. We show how these effects evolve as a function of disk and obstacle density, active run length, drift force, and motor force.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

Interstitial hydrogen enhances the mobility of some grain boundaries in tungsten

Segregation of interstitials at a grain boundary (GB) is known to generally lower its mobility. This phenomenon, called 'solute-drag', has important ramifications on the process of recrystallization and microstructural evolution. Here, we present predictions from molecular dynamics (MD) simulations which demonstrate that interstitial hydrogen in tungsten can in fact increase the mobility of some GBs which exhibit shear coupling. Assuming a disconnection-based mechanism, activation energies and pre-factors for disconnection nucleation are predicted from simulations of shear-coupled motion. In GBs where enhanced mobility is predicted, interstitial H reduces both the activation energy and the pre-factor for disconnection nucleation, thus effectively increasing the mobility. For GBs with diminished mobility, MD predicts that presence of interstitial H reduces the pre-factor and, in some cases, increases the activation energy. The reduction in the activation energy inferred from MD simulations are confirmed by nudged elastic band calculations. Temperature-dependent structural transitions are observed for some GBs, and the effect of interstitial H is found to change with the changes in structure. The effect of interstitial H is predicted to be complex and highly variable, providing some plausible explanations for experimental observations on the recrystallization of tungsten in presence of H-loaded plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2019

Determination of nanoparticle collision cross section distribution functions in low pressure plasma synthesis reactors via ion mobility spectrometry

Low pressure (< 20 Torr) non-thermal plasma flow tube reactors are often used for the synthesis of high purity nanoparticles (NPs) via nucleation and subsequent growth from vapor phase precursors. In spite of their utility, process monitoring (i.e. output NP size characterization) in such reactors is difficult, as there is a dearth of techniques available for online nanoparticle size distribution function measurement. In this study, we developed and applied an ion mobility spectrometry (IMS) system consisting of a low pressure differential mobility analyzer (LPDMA) and electrical detector to determine the collision cross section distribution functions of Si NPs synthesized in a radiofrequency non-thermal SiH4-Ar plasma operated at ~2 Torr (266 Pa). The collision cross section, roughly proportional to projected area, is a parameter quantifying the size and structure of nanometer scale species in the vapor phase. We introduce the collision cross section distribution function as a metric for potential use in online process monitoring in NP synthesis. Proper inversion of the collision cross section distribution function requires a priori knowledge of the LPDMA transfer function. We utilized a tandem differential mobility analyzer approach, coupled with a Twomey-Markwoski based scheme to determine LPDMA transfer functions. Subsequent application of these transfer functions in collision cross section distribution function determination showed that at the outlet of the non-thermal plasma flow tube reactor, both negatively and positively charged Si NPs persisted with nearly identical collision cross section distribution functions. NPs were found to have mode “mobility equivalent” diameters near 10 nm, and via TEM analysis were found to persist at the reactor outlet as small aggregates composed of ~5 nm diameter primary particles. Size distributions functions inferred from collision cross section measurements were compared to size distribution functions inferred from TEM images; excellent agreement was found between IMS and TEM for both mean mobility equivalent diameter and distribution function width. In total, this study shows that (1) IMS is a viable approach for process monitoring in non-thermal plasma NP flow tube synthesis systems, (2) although NPs are modestly aggregated at low-pressure plasma reactor outlets, the extent of aggregation is considerably less than observed in most atmospheric pressure and equilibrium NP synthesis systems (e.g. flames), and (3) after exiting the plasma reactor, the decharging of NPs from highly negatively charge states to a bipolar charge distribution likely drives aggregation on the plasma boundary.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

CORSAIR: A Framework for Human Mobility Prediction through Visit Characterization and Spatial Behavior Modeling

The rapid advancement of location acquisition technologies has led to the daily collection of vast amounts of mobile trajectory data, facilitating in-depth research on human mobility and enabling more accurate mobility prediction models. However, existing methodologies often fall short in capturing the intricate dynamics of human navigation and spatial behavior. This paper addresses this gap by exploring the multifaceted relationships between individuals and their environments, considering the diverse influences of personal preferences and experiences. Some places hold sentimental value and are visited frequently, while others serve as transient points of passage. To model these differences, we introduce CORSAIR, a novel visit characterization framework that leverages visitation patterns and dwell times to delineate an individual’s relationship with specific places. CORSAIR classifies visits into seven distinct types: casual, occasional, routine, special, anchor, important, and resettling. Also, we show that explicitly recognizing these distinct visit types and incorporating nuanced visit intents into mobility prediction models leads to a substantial improvement in prediction accuracy. This distinction allows for more precise modeling of the individual’s transitions, enhancing the personalization and relevance of location-based services. Our findings suggest that a deeper understanding of the complexities of individual-environment interactions is crucial for developing effective predictive tools in mobility research.

Amichi, Licia [ORNL] (ORCID:0000000177631394)↗

DOE OSTI2024

HumoNet: A Framework for Realistic Modeling and Simulation of Human Mobility Network

Understanding, analyzing, and predicting human mobility and dynamics are valuable to solving pressing problems, developing effective plans, and prescribing timely remedies. As a computational approach, realistic human mobility simulations allow us to understand, analyze, and predict complex systems, including human societies. Accurate simulations rely on (1) the model that captures interactions and behaviors of myriad entities in our society and (2) the mapping of model instances to real-world entities. Taking this into account, this paper introduces the Human Mobility Network simulation framework (HumoNet), an integrated patterns of life (POL) simulation framework that leverages real-world data layers including transportation networks, points of interest, populations, popularity, and human trajectories. HumoNet is a data informed model in which agents are equipped with activities, locomotion, and planning capabilities. To simulate realistic kinematic maneuvers of individuals in transportation networks, HumoNet harnesses a microscopic traffic simulator that provides interaction among vehicles and traffic objects. In this paper, we describe the framework, outline our methodologies, and discuss the data processing and challenges of each data layer. Through experiments, we demonstrate that our simulations capture key features of human mobility by comparing them to the literature and real data using standard measures of human mobility (i.e., the radius of gyration, number of locations visited, level of exploration) and metrics scoring (i.e., Jensen-Shannon divergence). We envision that the synthetic data produced by HumoNet will serve as a benchmark for analyzing epidemics, deploying EV charging networks, and validating AI/ML tasks such as location prediction.

Kim, Joon-Seok↗

DOE OSTI2020

High mobility in a van der Waals layered antiferromagnetic metal

Van der Waals (vdW) materials with magnetic order have been heavily pursued for fundamental physics as well as for device design. Despite the rapid advances, so far, they are mainly insulating or semiconducting, and none of them has a high electronic mobility—a property that is rare in layered vdW materials in general. The realization of a high-mobility vdW material that also exhibits magnetic order would open the possibility for novel magnetic twistronic or spintronic devices. Here, we report very high carrier mobility in the layered vdW antiferromagnet GdTe 3 . The electron mobility is beyond 60,000 cm 2 V –1 s –1 , which is the highest among all known layered magnetic materials, to the best of our knowledge. Among all known vdW materials, the mobility of bulk GdTe 3 is comparable to that of black phosphorus. By mechanical exfoliation, we further demonstrate that GdTe 3 can be exfoliated to ultrathin flakes of three monolayers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Activity Characterization for Modeling Behavioral-driven Human Mobility in Platial Networks

The population is increasingly becoming tractable as more and more people carry handheld devices as part of their everyday activities. Recent studies have shown that handheld devices' generated traffic share is now more than 50% of total global online traffic. This has created an unprecedented opportunity for modeling human mobility behavior. For example, aggregate check-ins and dwell time can reveal building level occupancies. However, there are clear limits to accurate modeling (e.g. reproducible, repeatable, and realistic), unless we decipher the underlying reason causing typical mobility patterns. We know that human behavior is a reflection of a set of activities, such as going to the gym or work, and which can be seen as a catalyst for humans to move from one location to another. This work envisions the use of activity characterization for modeling human mobility by introducing a context that maps activities to certain mobility patterns. In the end, we highlight the efficacy of the proposed approach by analyzing the impact of public policies surrounding stay at home order on human mobility.

Thakur, Gautam Malviya↗

DOE OSTI2023

A Design of Activity-Based Mobility Intervention

Human mobility influences our society and vice versa. During the COVID-19 pandemic, non-pharmaceutical intervention that alters activity-based mobility such as work-from-home greatly impacted human mobility patterns. Many studies on developing mitigation strategies have employed or implemented their own mobility intervention within their model assumption. For fair evaluation between intervention strategies across models, it is significant to set up compatible experimental environments. However, it is difficult to apply the identical intervention to different kinds of models and compare their effectiveness because each model might have different assumptions, capabilities, and implementations. Even if one can apply intervention to heterogeneous models, it may produce undesirable artifacts due to difference of models and integration with intervention. Therefore, minimizing undesirable artifacts and facilitating intervention experiments across heterogeneous models are substantial. Taking this into account, this paper investigates a design of activity-based mobility intervention (ABMI). We define ABMI together with related concepts and develop an extensible data model and schema of ABMI based on the 5W1H method that can be used in different models. As a case study, we apply the ABMI model to a micro-simulation to demonstrate the usability of the proposed model. We expect that standardized ABMI and interfaces may help to streamline development and experiments of intervention strategies across heterogeneous models.

Kim, Joon-Seok↗

DOE OSTI2022

Multisource Mobile Transfer Learning Algorithm Based on Dynamic Model Compression

With the development of the Internet of Things, the application of computer vision on mobile phones is becoming more and more extensive and people have higher and higher requirements for the timeliness of the recognition results returned and the processing capabilities of the mobile phone for image recognition. However, the processing capability and storage capability of the user terminal equipment cannot meet the needs of identifying and storing a large number of pictures, and the data transmission process will cause high energy consumption of the terminal equipment. At the same time, multisource deep transfer learning has outstanding performance in computer vision and image classification. However, due to the huge amount of calculation of the deep network model, it is impossible to use the existing excellent network model to realize image recognition and classification on the mobile terminal. In order to solve the abovementioned problems, we propose a multisource mobile transfer learning algorithm based on dynamic model compression, this algorithm considers the realization of multisource transfer learning computing in the case of multiple mobile device computing source domains, and the method also guarantees data privacy and security for each device (origin domain). Meanwhile, extensive experiments show that our method can achieve remarkable results in popular image classification datasets.

Gao, Peng↗

DOE OSTI2021

The Transportation Energy and Mobility Pathway Options (TEMPO) Model: Overview and Validation of V1.0 [Slides]

This presentation documents the approaches and methods used in the Transportation Energy & Mobility Pathway Options™ (TEMPO) model to evaluate passenger and freight demand for transportation and mobility services, project vehicle ownership and technology adoption decisions, and determine transport mode choices to derive scenarios of future energy use and emissions. TEMPO is an all-inclusive transportation demand model that covers the entire United States, with an implicit spatial resolution and an hourly temporal resolution that allows for generating time-resolved energy use profiles to assess multisectoral integration aspects. Key features of the TEMPO model include the ability to perform endogenous out-of-sample forecasting to extrapolate recent emerging trends and analyze impacts of disruptive technological breakthroughs and behavioral changes. TEMPO employs an innovative representation of passenger mobility demand stemming from household-level decisions that determine vehicle adoption, ownership, and use based on sociodemographics (e.g., income, household composition), technology attributes (e.g., travel cost, time), geography (e.g., urban, suburban, rural) and population-specific multiday mobility and travel requirements. This representation enables a more forward-looking perspective on the use of new mobility options and the adoption of alternative fuel vehicles, as well as a more accurate representation of their energy usage profiles than previous modeling approaches. A comparison with the U.S. Energy Information Administration’s Annual Energy Outlook showcases the ability of TEMPO to accurately replicate widely accepted projections by representing the key elements of the entire transportation sector at the appropriate level of resolution. TEMPO is intended to generate future scenarios of technology adoption, energy use, and emissions in the transportation sector to compare alternatives, inform decision makers, and assess integration with energy infrastructure and supply systems at an appropriate spatiotemporal resolution.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

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↗

DOE OSTI2019

Molecular Dynamics Calculations of Grain Boundary Mobility in CdTe

Molecular dynamics (MD) simulations have been applied to study mobilities of Σ3, Σ7 and Σ11 grain boundaries in CdTe. First, an existing MD approach to drive the motion of grain boundaries in face-centered-cubic and body-centered-cubic crystals was generalized for arbitrary crystals. MD simulations were next performed to calculate grain boundary velocities in CdTe crystals at different temperatures, driving forces, and grain boundary terminations. Here a grain boundary is said to be Te-terminated if its migration encounters sequentially C d · T e − C d · T e … planes, where “·” and “−” represent short and long spacing respectively. Likewise, a grain boundary is said to be Cd-terminated if its migration encounters sequentially T e · C d − T e · C d … planes. Grain boundary mobility laws, suitable for engineering time and length scales, were then obtained by fitting the MD results to Arrhenius equation. These studies indicated that the Σ3 grain boundary has significantly lower mobility than the Σ7 and Σ11 grain boundaries. The Σ7 Te-terminated grain boundary has lower mobility than the Σ7 Cd-terminated grain boundary, and that the Σ11 Cd-terminated grain boundary has lower mobility than the Σ11 Te-terminated grain boundary.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Rapid measurement of RH-dependent aerosol hygroscopic growth using a humidity-controlled fast integrated mobility spectrometer (HFIMS)

Abstract. The ability of aerosol particles to uptake water (hygroscopic growth) is an important determinant of aerosol optical properties and radiative effects. Aerosol hygroscopic growth is traditionally measured by humidified tandem differential mobility analyzers (HTDMA), in which size-selected dry particles are exposed to elevated relative humidity (RH), and the size distribution of humidified particles is subsequently measured using a scanning mobility particle sizer. As a scanning mobility particle sizer can measure only one particle size at a time, HTDMA measurements are time consuming, and ambient measurements are often limited to a single RH level. Pinterich et al. (2017b) showed that fast measurements of aerosol hygroscopic growth are possible using a humidity-controlled fast integrated mobility spectrometer (HFIMS). In HFIMS, the size distribution of humidified particles is rapidly captured by a water-based fast integrated mobility spectrometer (WFIMS), leading to a factor of ∼10 increase in measurement time resolution. In this study we present a prototype HFIMS that extends fast hygroscopic growth measurements to a wide range of atmospherically relevant RH values, allowing for more comprehensive characterizations of aerosol hygroscopic growth. A dual-channel humidifier consisting of two humidity conditioners in parallel is employed such that aerosol RH can be quickly stepped among different RH levels by sampling from alternating conditioners. The measurement sequence is also optimized to minimize the transition time between different particle sizes. The HFIMS is capable of measuring aerosol hygroscopic growth of six particle diameters under five RH levels ranging from 20 % to 85 % (30 separate measurements) every 25 min. The performance of this HFIMS is characterized and validated using laboratory-generated ammonium sulfate aerosol standards. Measurements of ambient aerosols are shown to demonstrate the capability of HFIMS to capture the rapid evolution of aerosol hygroscopic growth and its dependence on both size and RH.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1972

Mobilities of uranium and mercury ions in helium

The mobilities of mass-identified U(+) and Hg (+) ions in helium were determined in a drift tube-mass spectrometer. For uranium ions, a reduced mobility value is obtained at 305 K and a standard gas density of 2.69 x 10 to the 19th power/cu cm. The mobility of mercury ions is in agreement with two previous determinations. The effect of fast ion injection in drift mobility measurements is discussed, and a technique to circumvent these problems is described. The results are compared with existing theories of ion mobilities.

Johnsen, R.↗

NASA NTRS1975

Skylab mobile laboratory

The Skylab mobile laboratory was designed to provide the capability to obtain necessary data on the Skylab crewmen 30 days before lift-off, within 1 hour after recovery, and until preflight physiological baselines were reattained. The mobile laboratory complex consisted of six laboratories that supported cardiovascular, metabolic, nutrition and endocrinology, operational medicine, blood, and microbiology experiments; a utility package; and two shipping containers. The objectives and equipment requirements of the Skylab mobile laboratory and the data acquisition systems are discussed along with processes such as permanently mounting equipment in the individual laboratories and methods of testing and transporting the units. The operational performance, in terms of amounts of data collected, and the concept of mobile laboratories for medical and scientific experiments are evaluated. The Skylab mobile laboratory succeeded in facilitating the data collection and sample preservation associated with the three Skylab manned flights.

Primeaux, G. R.↗

NASA NTRS1976

Automatic control of a mobile Viking lander on the surface of Mars

A mobile lander system is being considered for use in a possible follow-on mission to the Viking '75 landings on Mars. A mobile Viking lander, which could be launched as early as the 1979 opportunity, would be capable of traversing 100 m to 1 km per day on a commanded heading while sensing hazards and performing avoidance maneuvers. The degree of autonomous control, and consequently the daily traverse range, is still under study. The mobility concept requires the addition of: (1) track-laying or wheel units in place of the Viking Lander footpads, (2) a set of hazard and navigation sensors, and (3) a mobility control computer capability. The technology required to develop these three subsystems is available today. The principal objective of current design studies, as described in this paper, is to define a mobile lander system that will demonstrate high reliability and fail-safe hazard avoidance while achieving range- and terrain-handling capabilities which satisfy the Mars exploration science requirements.

Moore, J.↗

NASA NTRS1984

Rural land mobile radio market assessment and satellite and terrestrial system concepts

The market for satellite-based mobile radio in the rural U.S. is evaluated, summarizing the results of two NASA-funded studies reported by Anderson et al. and Hornstein. The study aims are listed, and the results are presented in tables, graphs, and maps and discussed. Space systems are found to be competitive with land-based systems, providing superior service at lower subscriber charges, but having limited compatibility with urban cellular mobile-radio systems. Of the three system concepts evaluated from a technological standpoint (direct-to-mobile, mobile-translator, and hybrid), the mobile-translator concept is considered most cost effective, at least within the constraints assumed in the study.

Stevenson, S.↗