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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

High-Fidelity Modeling of Curbside Driving Behavior in SUMO: Preprint

Recent advances in mobility technologies have considerably increased the need for curbside use and congestion at curb-lanes. At airports and in dense urban centers, the growing adoption of Transportation Network Companies (TNCs), such as Uber and Lyft, has led to an increase in curbside traffic due to the reduction in the use public transit and other shared modes. In dense city areas, the curbside demand and congestion were further augmented by the growing use of e-commerce, which requires home-delivery of goods. To model vehicles' curbside interactions realistically, there is a need for high-fidelity simulation models that can represent the complex interplay of vehicles as they complete pick-up or drop-off trips. Vehicles' curbside behaviors are usually not modeled with high-fidelity in microscopic simulators such Simulation of Urban of Mobility (SUMO). This paper presents such a high-resolution model for vehicle curbside behavior in SUMO, using SUMO's Traci interface. Simulations results demonstrate that the improved curbside behavior captures vehicles' curbside maneuvering more accurately than the default SUMO curbside model, and increases the curbside utilization and capacity.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Exploring the Utility-Privacy Trade-Off: Impacts of Semantic and Visit Types Ambiguities on Human Mobility Simulation

Humans are in perpetual movement, constantly traversing buildings, cities, waters, oceans, and countries. Mobility stands out as a major driving force shaping our modern societies. Capturing and explaining human behavior in a world of eight billion distinct mobility agendas is a complex challenge. With the rise of interconnected devices and platforms, such as smartphones, wearables, and point-of-interest data, largescale behavioral data has become more accessible, enabling rich insights into mobility patterns. However, the widespread availability of such data introduces significant ethical challenges. Detailed mobility data can inadvertently reveal sensitive personal information, including individuals' locations, habits, social interactions, and even political or religious affiliations. Beyond privacy breaches, the ethical implications of uncovering and potentially manipulating underlying behavioral patterns demand attention. Striking a balance between the utility of mobility models and the protection of individual privacy is therefore paramount. This paper explores the utility-privacy trade-offs in human mobility modeling, focusing on the impacts of introducing semantic and visit type ambiguities. By systematically examining how these ambiguities affect the fidelity of simulated trajectories and privacy risks, we provide a framework for evaluating ethical and privacy-conscious modeling practices. Our findings emphasize the need for methods that safeguard privacy without undermining the usefulness of mobility models, contributing to the responsible advancement of mobility science in alignment with ethical standards and societal expectations.

Amichi, Licia [ORNL] (ORCID:0000000177631394)↗
DOE OSTI2021

Unraveling the hysteretic behavior at double cations-double halides perovskite - electrode interfaces

Despite over a decade of research on metal halide perovskites (MHPs) in the context of photovoltaic applications, understanding the nature of electronic and ionic processes associated with current-voltage (I-V) hysteretic behavior has been limited. Here, we explore the hysteretic behavior in (FAPbI 3 ) 0.85 (MAPbBr 3 ) 0.15 perovskite devices with lateral Cr electrodes by applying first order reversal curve (FORC) bias waveform in I-V, Kelvin probe force microscopy (KPFM) measurements, and in-situ chemical imaging by time-resolved time-of-flight secondary ion mass spectrometry (tr-ToF-SIMS). In dark, we reveal pronounced hysteretic behaviors of charge dynamics in the off-field by probing time-dependent current and contact potential difference (CPD). Under illumination, transient and hysteretic behaviors are significantly reduced. The tr-ToF-SIMS results reveal that the hysteretic behaviors are strongly associated with accumulation of Br- ions at the interfaces. In addition, the low mobility MA + ions result in transient behavior and contribute to the hysteretic phenomena. It was shown that Pb 2+ ions can be reduced at the interfaces due to electrochemical reactions with the electrode in the presence of charge injection and photogenerated charges. Furthermore, these hysteretic behaviors associated with charge dynamics, ion migration, and interfacial electrochemical reaction are critical to further improve the performance and stability of MHPs photovoltaics and optoelectronics.

42 ENGINEERING↗
DOE OSTI2025

Stability of aqueous neodymium complexes in carbonate-bearing solutions from 100–600 °C

Rare earth element exploration requires a quantitative understanding of factors governing their mobilization and economic concentration. However, the behavior of rare earth elements in carbonate- bearing hydrothermal fluids associated with carbonatite-hosted deposits is poorly understood, and conflicting mechanisms of rare earth transport by anionic ligands and alkali behavior have been described. Here, we report quantitative data to characterize the role of carbonate-bearing solutions in the hydrothermal mobilization of neodymium. Solubility studies of neodymium phosphate were performed at temperatures ranging from 100 to 600 °C in carbonate-bearing solutions. The thermodynamic data determined for the predominant complex were used to model the separation of neodymium from thorium in a simple flow-through system based on fluid and mineral compositions characteristic of carbonatite deposits. Our data suggest that neodymium transport is controlled by the stability of the carbonate species NdCO 3 OH o , and at temperatures of 500–600 °C, the concentrations of neodymium in solutions can reach ~1000 ppm.

58 GEOSCIENCES↗
DOE OSTI2021

The CanBikeCO Mini Pilot: Preliminary Results and Lessons Learned

In fall 2020, the Colorado Energy Office, as part of the State of Colorado’s “Can Do Colorado” initiative, initiated a project aimed at encouraging energy-efficient transportation during the COVID-19 pandemic. The initial mini-pilot provided e-bikes to 13 low-income households under an individual ownership model. This report assesses the impact of providing this additional mobility option on the travel behavior of participants. It also outlines the lessons learned from deploying a continuous monitoring platform to track the travel behavior. These lessons will influence the evaluation component for the full pilot, which will cover multiple geographic regions, starting in summer 2021, and run for 2 years. The continuous data collection was enabled by a customized version of the open-source e-mission platform, called CanBikeCO, configured with a behavioral gamification feature. The Colorado Energy Office used this system to collect a unique data set consisting of 3 months of partially automated travel diaries, combining sensed and surveyed data and linked with demographic information, from 12 participants. The data collection process worked well overall: users generally liked the app, appreciated the game, and did not complain about battery life. The long tracking period introduced behavioral challenges in user engagement, which we plan to address using repeated patterns and automated status checks for the full pilot. The analysis results, based on the subset of trips with user-reported labels (68%), indicate that the e-bike was the dominant commute mode share (31%), in sharp contrast to the census bicycle commute mode share (<1%). E-bike trips primarily replaced single-occupancy vehicle (SOV) trips (28%), followed closely by walking (24%) and regular bike (20%). The nonmotorized mode replacement corresponds to lower travel time and increased productivity enabled by the program. The emissions impact analysis of the program, computed using trip-level energy intensity factors, indicates savings of 1,367 lbs. of CO 2 . Although the results are strongly positive, the narrow demographic profile of study participants, their limited mobility alternatives, and nonuniform labeling indicate caution in broader interpretation. These preliminary results do suggest that such programs, supported by real-time education and support from program managers, can simultaneously meet equity and sustainability goals. The planned full pilot, addressing the data collection challenges and broadening the geographic scope, will provide additional insights into the generality of this approach.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

The CanBikeCO Mini Pilot: Procedure and Preliminary Results

In fall 2020, the Colorado Energy Office, as part of the State of Colorado's "Can Do Colorado" initiative, initiated a project aimed at encouraging energy-efficient transportation during the COVID-19 pandemic. The initial mini-pilot provided e-bikes to 13 low-income households under an individual ownership model. This report assesses the impact of providing this additional mobility option on the travel behavior of participants. It also outlines the lessons learned from deploying a continuous monitoring platform to track the travel behavior. These lessons will influence the evaluation component for the full pilot, which will cover multiple geographic regions, start in summer 2021, and run for 2 years. The continuous data collection was enabled by a customized version of the open-source e-mission platform, called CanBikeCO, configured with a behavioral gamification feature. The Colorado Energy Office used this system to collect a unique data set consisting of 3 months of partially automated travel diaries, combining sensed and surveyed data and linked with demographic information, from 12 participants. The data collection process worked well overall: users generally liked the app, appreciated the game, and did not complain about battery life. The long tracking period introduced behavioral challenges in user engagement, which we plan to address using repeated patterns and automated status checks for the full pilot. The analysis results, based on the subset of trips with user-reported labels (68%), indicate that the e-bike was the dominant commute mode share (31%), in sharp contrast to the census bicycle commute mode share (<1%). E-bike trips primarily replaced single-occupancy vehicle (SOV) trips (28%), followed closely by walking (24%) and regular bike (20%). The non-motorized mode replacement corresponds to lower travel time and increased productivity enabled by the program. The emissions impact analysis of the program, computed using trip-level energy intensity factors, indicates savings of 1,367 lbs. of CO2. Although the results are strongly positive, the narrow demographic profile of study participants, their limited mobility alternatives, and nonuniform labeling indicate caution in broader interpretation. These preliminary results do suggest that such programs, supported by real-time education and support from program managers, can simultaneously meet equity and sustainability goals. The planned full pilot, addressing the data collection challenges and broadening the geographic scope, will provide additional insights into the generality of this approach.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Mining and Validating Social Media Data for COVID-19–Related Human Behaviors Between January and July 2020: Infodemiology Study

Background: Health authorities can minimize the impact of an emergent infectious disease outbreak through effective and timely risk communication, which can build trust and adherence to subsequent behavioral messaging. Monitoring the psychological impacts of an outbreak, as well as public adherence to such messaging, is also important for minimizing long-term effects of an outbreak. Objective: We used social media data from Twitter to identify human behaviors relevant to COVID-19 transmission, as well as the perceived impacts of COVID-19 on individuals, as a first step toward real-time monitoring of public perceptions to inform public health communications. Methods: We developed a coding schema for 6 categories and 11 subcategories, which included both a wide number of behaviors as well codes focused on the impacts of the pandemic (eg, economic and mental health impacts). We used this to develop training data and develop supervised learning classifiers for classes with sufficient labels. Classifiers that performed adequately were applied to our remaining corpus, and temporal and geospatial trends were assessed. We compared the classified patterns to ground truth mobility data and actual COVID-19 confirmed cases to assess the signal achieved here. Results: We applied our labeling schema to approximately 7200 tweets. The worst-performing classifiers had F1 scores of only 0.18 to 0.28 when trying to identify tweets about monitoring symptoms and testing. Classifiers about social distancing, however, were much stronger, with F1 scores of 0.64 to 0.66. We applied the social distancing classifiers to over 228 million tweets. We showed temporal patterns consistent with real-world events, and we showed correlations of up to –0.5 between social distancing signals on Twitter and ground truth mobility throughout the United States. Conclusions: Behaviors discussed on Twitter are exceptionally varied. Twitter can provide useful information for parameterizing models that incorporate human behavior, as well as for informing public health communication strategies by describing awareness of and compliance with suggested behaviors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Chalcogenide perovskite BaZrS 3 thin-film electronic and optoelectronic devices by low temperature processing

Owing to its superior visible light absorption and high chemical stability, chalcogenide perovskite barium zirconium sulfide (BaZrS 3 ) has attracted significant attention in the past few years as a potential alternative to hybrid halide perovskites for optoelectronics. However, the high processing temperatures of BaZrS 3 thin films at above 1000 °C severely limits their potential for device applications. Herein, we report the synthesis of BaZrS 3 thin films at temperatures as low as 500 °C, by changing the chemical reaction pathway. The single phase BaZrS 3 thin film was confirmed by X-ray diffraction and Raman spectroscopy. Atomic force microscopy and scanning electron microscopy show that crystalline size and surface roughness were consistently reduced with decreasing annealing temperature. The lower temperatures further eliminate sulfur vacancies and carbon contaminations associated with high temperature processing. The ability to synthesize chalcogenide perovskite thin films at lower temperatures removes a major hurdle for their device fabrication. The photodetectors demonstrate fast response and an on/off ratio of 80. Finally, the fabricated field effect transistors show an ambipolar behavior with electron and hole mobilities of 16.8 cm 2 /Vs and 2.6 cm 2 /Vs, respectively.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Ion dynamics in hexagonal boron nitride ionogel electrolytes

Ionogel electrolytes incorporating exfoliated hexagonal boron nitride (hBN) nanoplatelets are promising materials for next-generation energy storage systems. However, detailed understanding of their ion transport properties at the molecular level remains limited. This study employs diffusion and relaxation nuclear magnetic resonance (NMR) techniques, including fast-field cycling (FFC) NMR, to investigate the dynamics of ionic species in hBN-ionogels. By spanning a broad frequency range from 30 kHz using FFC NMR to high-field NMR (500–800 MHz), we reveal distinct relaxation mechanisms governing ion dynamics in ionogels with and without lithium salts. Our results highlight the role of hBN in modulating molecular rotation and translational motion, significantly affecting 1 H and 19 F relaxation profiles. The presence of Li + alters the dynamic behavior in ionogels, enhancing anion mobility at the interface. Notably, 7 Li relaxation reveals strong interactions with the hBN surface that cannot be detected by diffusion NMR. Furthermore, these findings underscore the importance of spanning a broad frequency range in NMR studies of ionogels and provide critical insights into optimizing their design as novel electrolytes.

Electrolytes↗
DOE OSTI2022

Shifting temporal dynamics of human mobility in the United States

In this paper we analyze the average hourly temporal dynamics of human mobility in the United States from 2019 to 2020. We discuss how large decreases in human mobility nonuniformly effect the daily temporal dynamics of aggregate human behavior. The data used are weekly activity patterns for POIs from 2019 to 2020 in the United States, provided by SafeGraph and made openly available to academic and research institutions. We use clustering methods to create metrics describing how human activity changes throughout the day/week at the county and national levels. In response to significant mobility reductions starting March 2020, daily temporal patterns of human activity changed nonuniformly. Morning activity started later, and evening activity started earlier in 2020 compared to 2019, and temporal behavioral patterns on weekdays began to look more similar to weekends. The changes in daily temporal behavior persisted throughout the year even as total mobility levels recovered. The results provide insights on the changes in human behavior in response covid-19 policies and illustrate influences on social systems, health, and transportation networks.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Elucidating the Gas-Phase Behavior of Nitazene Analog Protomers Using Structures for Lossless Ion Manipulations Ion Mobility-Orbitrap Mass Spectrometry

2-benzylbenzimidazoles, or “nitazenes”, are a class of novel synthetic opioids (NSOs) that are increasingly being detected alongside fentanyl analogs and other opioids in drug overdose cases. Nitazenes can be 20x more potent than fentanyl but are not routinely tested for during postmortem or clinical toxicology drug screens; thus, their prevalence in drug overdose cases may be under-reported. Traditional analytical workflows utilizing liquid chromatography-tandem mass spectrometry (LC-MS/MS) often require additional confirmation with authentic reference standards to identify a novel nitazene. However, additional analytical measurements with ion mobility spectrometry (IMS) may provide a path towards reference-free identification, which would greatly accelerate NSO identification rates in toxicology labs. Presented here are the first IMS and collision cross section (CCS) measurements on a set of fourteen nitazene analogs using a Structures for Lossless Ion Manipulations (SLIM)-Orbitrap MS. All nitazenes exhibited two high intensity baseline-separated IMS distributions, which fentanyls and other drug and drug-like compounds also exhibit. Incorporating water into the electrospray ionization (ESI) solution caused the intensities of the higher mobility IMS distributions to increase the intensities of the lower mobility IMS distributions to decrease. Nitazenes lacking a nitro group at the R1 position exhibited the greatest shifts in signal intensities due to water. Furthermore, IMS-MS/MS experiments showed that the higher mobility IMS distributions of all nitazenes produced fragment ions with m/z 72, 100, and other low intensity fragments while the lower mobility IMS distributions only produced fragment ions with m/z 72 and 100. The IMS, solvent, and fragmentation studies provide experimental evidence that nitazenes potentially exhibit three gas-phase protomers. In conclusion, the cyclic IMS capability of SLIM was also employed to partially resolve four sets of structurally similar nitazene isomers (e.g., protonitazene/isotonitazene, butonitazene/isobutonitazene/secbutonitazene), showcasing the potential of using high-resolution IMS separations in MS-based workflows for reference-free identification of emerging nitazenes and other NSOs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

TSDC: Transportation Secure Data Center: Real-World Data for Planning, Modeling, and Analysis

The Transportation Secure Data Center is a centralized repository for high-resolution transportation data from hundreds of travel and transit surveys and studies. It makes vital transportation data broadly available to users while preserving the privacy of survey participants. It houses surveys and studies conducted by state departments of transportation, metropolitan planning organizations, transit agencies, cities, and other public agencies. Meanwhile, the Livewire Data Platform empowers research, industry, and academic partners to easily and securely preserve, maintain, share, discover, and gain access to transportation and mobility data. Livewire accommodates a range of datasets, including behavioral, experimental, model, analytical, and raw data at the vehicle, traveler, and system levels. Datasets support mobility research and planning spanning urban science, connected and automated vehicles, fueling and charging infrastructure, mobility decision science, multimodal transportation, vehicle efficiency, and more.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

A Customizable Metric to Provide a Comprehensive Picture of the Mobility Potential of a Location

Accessibility in a geo-spatial context refers to the ease of reaching a variety of opportunities from a given location. Accessibility theories (and resulting metrics) have traditionally focused on quantifying access to specific opportunities (such as jobs), or focused on specific modes (such as car, bike, etc.). Such approaches often fall short of providing a comprehensive picture of the true accessibility potential of a location as a combination of multiple modes to multiple types of destinations. Addressing this drawback, a novel metric labeled the ‘Mobility Energy Productivity (MEP) Metric’ was developed at the National Renewable Energy Laboratory to quantify the mobility potential of a location to connect people to goods, services, and employment using a variety of modes, while accounting for time, energy, and affordability. The MEP metric has been integrated with advance travel behavior models to compute the changes in mobility potential for various future scenarios, such as introduction of automated vehicles, and/or electric vehicles—but does so at the aggregate, or average-citizen level. The MEP in its initial iteration is not customized to the particular socio-economic contingents, or even to an individual whose modal availability or pattern of trip making may substantially differ from the average. Addressing this gap, this research effort extends the MEP framework from a static state to a more tailored and dynamic state, one in which an individual, or group can customize the metric for their unique characteristics, such as modes, activity patterns, and time-of-day preferences. The extended MEP metric framework can now be integrated to assess the customized mobility energy productivity of an individual.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2024

From roads to roofs: How urban and rural mobility influence building energy consumption

In this article, understanding the relationship between travel behavior and building energy use at an urban scale is crucial for developing effective energy management strategies. Mobility patterns significantly impact building occupancy, which in turn affects energy consumption. However, existing methods often focus on individual buildings, whereas geographical influences on energy usage are not adequately examined. This study addresses this gap by using transportation origin-destination (OD) data to estimate building occupancy and energy. The proposed method assigns OD trips from census block groups to the building level, incorporating building, travel survey, and census data to derive building occupancy profiles. This method was applied to urban and rural areas with 4062 buildings in 70 census block groups. We found that the OD-informed occupancy profile exhibits smoother energy consumption patterns compared with that of Department of Energy reference occupancy profiles. Our analysis reveals distinct building energy consumption patterns among groups with long and short commutes, emphasizing the effect of commute times and work schedules on residential energy usage. This framework is useful for practitioners in transportation agencies and utility companies, enabling the estimation of building energy based on mobility patterns. Overall, this study shows the potential of integrating transportation and building energy data to inform cross-sector energy management strategies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

What Makes You Hold on to That Old Car? Joint Insights From Machine Learning and Multinomial Logit on Vehicle-Level Transaction Decisions

What makes you hold on to that old car? While the vast majority of household vehicles are still powered by conventional internal combustion engines, the progress of adopting emerging vehicle technologies will critically depend on how soon the existing vehicles are transacted out of the household fleet. Leveraging a nationally representative longitudinal data set, the Panel Study of Income Dynamics, this study examines how household decisions to dispose of or replace a given vehicle are: 1) influenced by the vehicle’s attributes, 2) mediated by households’ concurrent socio-demographic and economic attributes, and 3) triggered by key life cycle events. Coupled with a newly developed machine learning interpretation tool, TreeExplainer, we demonstrate an innovative use of machine learning models to augment traditional logit modeling to both generate behavioral insights and improve model performance. We find the two gradient-boosting-based methods, CatBoost and LightGBM, are the best performing machine learning models for this problem. The multinomial logistic model can achieve similar performance levels after its model specification is informed by TreeExplainer. Both machine learning and multinomial logit models suggest that while older vehicles are more likely to be disposed of or replaced than newer ones, such probability decreases as the vehicles serve the family longer. Pickup trucks and sport utility vehicles are less likely to be disposed of or replaced than cars, and leased vehicles are more likely to be transacted than owned vehicles. We find that married families, families with higher education levels, homeowners, and older families tend to keep their vehicles longer. Life events such as childbirth, residential relocation, and change of household composition and income are found to increase vehicle disposal and/or replacement. We provide additional insights on the timing of vehicle replacement or disposal, in particular, the presence of children and childbirth events are more strongly associated with vehicle replacement among younger parents.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Highly Responsive Near-Infrared Photodetector Based on Contactless PdSe 2 Integration with a Few-Layered MoSe 2 Field-Effect Transistor

Two-dimensional (2D) semiconductors with narrow bandgaps are promising candidates for near- and far-infrared (IR) photodetection, particularly in the telecommunication spectral window. However, current low-bandgap IR photodetectors face significant challenges due to their high dark current, increased carrier recombination, and thermally generated noise. Here, in this work, a hybrid phototransistor is demonstrated by integrating direct, contact-free palladium diselenide (PdSe 2 ) as a highly responsive IR detection layer with a non-IR-absorbing molybdenum diselenide (MoSe 2 ) field-effect transistor (FET), using a near-IR source at a wavelength of λ = 1650 nm. Exfoliated PdSe 2 flakes integrated into a back-gated FET architecture exhibit ambipolar transport behavior, with extracted hole and electron mobilities of 24.8 cm 2 V –1 s –1 and 58.4 cm 2 V –1 s –1 , respectively. The devices show a clear photocurrent generation under the illumination of a λ = 1650 nm laser source, achieving a notable responsivity of ∼300 mA W -1 at an applied gate voltage of 15 V, which highlights the suitability of PdSe 2 as a narrow-bandgap material for photodetection. Photoresponsivity saturates and does not have any effect above an applied gate voltage of 15 V. To further tune the photoresponsivity performance continuously with the applied gate voltage, we construct a van der Waals heterostructure phototransistor, where few layers of PdSe 2 are directly transferred onto the 2D channel region of a MoSe 2 FET, while avoiding any contact with the metal electrodes. In this heterostructure, PdSe 2 works as the primary active IR-absorbing layer, while MoSe 2 provides high-performance FET characteristics. This spatial separation of absorption and transport facilitates efficient interlayer charge transfer and charge separation, resulting in high responsivities of up to 972 mA W –1 at near-IR wavelengths and a low power density of 1.5 mW/mm 2 . The responsivity of our photodetector is comparable to that of some state-of-the-art commercially available NIR photodetectors, highlighting the potential of PdSe 2 -based heterostructures as scalable, CMOS-compatible platforms for high-performance near-IR detection.

Infrared (IR) photodetectors↗
DOE OSTI2023

Structural Characterization of Toxicologically Relevant Cd 2+ -L-Cysteine Complexes

The exposure of humans to Cd exerts adverse human health effects at low chronic exposure doses, but the underlying biomolecular mechanisms are incompletely understood. To gain insight into the toxicologically relevant chemistry of Cd 2+ in the bloodstream, we employed an anion-exchange HPLC coupled to a flame atomic absorption spectrometer (FAAS) using a mobile phase of 100 mM NaCl with 5 mM Tris-buffer (pH 7.4) to resemble protein-free blood plasma. The injection of Cd 2+ onto this HPLC-FAAS system was associated with the elution of a Cd peak that corresponded to [CdCl 3 ] - /[CdCl 4 ] 2- complexes. The addition of 0.1–10 mM L-cysteine (Cys) to the mobile phase significantly affected the retention behavior of Cd 2+ , which was rationalized by the on-column formation of mixed CdCysxCly complexes. From a toxicological point of view, the results obtained with 0.1 and 0.2 mM Cys were the most relevant because they resembled plasma concentrations. The corresponding Cd-containing (~30 μM) fractions were analyzed by X-ray absorption spectroscopy and revealed an increased sulfur coordination to Cd 2+ when the Cys concentration was increased from 0.1 to 0.2 mM. The putative formation of these toxicologically relevant Cd species in blood plasma was implicated in the Cd uptake into target organs and underscores the notion that a better understanding of the metabolism of Cd in the bloodstream is critical to causally link human exposure with organ-based toxicological effects.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Segmenting the target audience for transportation demand management programs: An investigation between mode shift and individual characteristics

Understanding the characteristics of travelers and situations that are more likely to switch from single occupancy vehicles (SOV) to more sustainable mobility options can help transportation agencies develop better behavior change strategies. Existing mode shift programs, however, rarely identify their target audience, which could make the programs less effective. Here, to investigate the demographics and trip characteristics of those who are more likely to shift from SOV to carpooling, public transit, and micromobility (e.g. walking, biking), a matrix decomposition audience segmentation method is proposed and applied on travel survey data. The results of this research show that for short-distance leisure or social trips, young and middle-income people are more likely to shift to these mobility options from SOV. This study provides a comprehensive and profound understanding of the characteristics of the target audience that can inform policies to create more targeted behavior change strategies to reach their sustainability goals.

42 ENGINEERING↗