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At least 19 records

Metastable Clusters and Competitive Solvation Tune Ion Pairing at Liquid Interfaces

The balance of hydrophobic and hydrophilic interactions underlies emergent phenomena in complex multicomponent chemical systems. Here, we show that a supposedly ‘non–interacting’ nonpolar phase can be used to competitively solvate amphiphilic molecules at an oil/aqueous interface. This solvation, as probed by surface specific nonlinear spectroscopy and simulations, results in a molecularly thin corrugated phase boundary featuring metastable assemblies that alter the hydrogen bonding networks of water and the apparent ‘hard/soft’ descriptors used to describe ionic interactions. We show that competitive solvation enhances amphiphile mobility, opening up otherwise energetically inaccessible complexes that transiently interact with aqueous phase ions. These transient species impact ensemble binding affinities and may represent the molecular agents responsible for aspects of ionic transport and function. In conclusion, the result of this work highlights how seemingly unrelated nonpolar interactions feedback onto aqueous phase chemical phenomena, providing a pathway to tune phase separation and self-assembly to access new reaction pathways using interfaces for a range of chemical and biological systems.

Anions↗

Navigating Urban Mobility: Evaluating Infrastructure Strategies for Enhanced Energy-Efficient Access for Micromobility

Cities and communities continue to expand pedestrian and bicycle infrastructure as part of their sustainable mobility and post-pandemic recovery plans. However, the emergence of micro-mobility (e.g., electric bicycles) has created new challenges for urban transport planning. As the popularity of micro-mobility modes has grown, so have safety concerns due to rising injuries, thus challenging many cities to come up with regulatory measures that enable efficient access while minimizing negative impacts from micro-mobility. Leveraging the Open-Source Tool (Mobility Energy Productivity metric), powered by an open-source dataset (OpenStreetMap), and enhanced through the incorporation of perceived discomfort (level-of-traffic stress), this research study focuses on evaluating the accessibility implications of infrastructure planning and regulatory measures for micro-mobility. Five scenarios pertaining to level of traffic stress, sidewalk access, traffic calming, and bike lane coverage were tested in the Denver-Aurora region in Colorado. Maximum improvements in energy-efficient access are realized when allowing sidewalks for micro-mobility use. Cities and planning agencies could leverage this information to assess sidewalk use policies for micro-mobility, while ensuring pedestrian safety and ADA access. Results indicate that expansion of bicycle lane coverage yields 11% accessibility benefits for micro-mobility compared to implementing traffic calming measures yielding 3% accessibility improvements. Further, it was observed most of the population in the Denver-Aurora region is experiencing lower accessibility in-part due to presence of a high-stress connections in the network. Although not generalizable, the use of open-source data and access calculation methodology, make this analysis reproducible and transferable to other locations.

ADVANCED PROPULSION SYSTEMS↗

Creating the First Interactive Mobility Data Landscape

As the world continues to be driven increasingly driven by data, the ways this data is sorted and collected is critical for researchers and specification creators. In the world of mobility data, there are few if any de jure standards connecting data, and there is little knowledge on the gaps that exist in the data. In this project we have created an interactive landscape where mobility data and data specifications can be categorized and organized in an easy-to-use living document.

ADVANCED PROPULSION SYSTEMS↗

A comprehensive diffusion mobility database comprising 23 elements for magnesium alloys

We report that reliable experimental diffusion coefficients of 10 key alloying elements in Mg obtained by the present authors together with experimental data in the literature enabled us to perform a systematic test of the reliability of diffusion coefficients obtained from DFT calculations. The computed activation energy values were found to be quite accurate (mostly within 0.2 eV) but the computed pre-factors were less reliable. Such insights allowed us to develop a practical and yet robust strategy to perform diffusion mobility assessments by adopting the computed activation energy while fitting only the pre-factor when available experimental data are limited to a narrow temperature range. The overall good agreement between the DFT data and experimental data also gave us the confidence to employ the computed data for those that were still missing or inaccessible from experimental measurements. A systematic assessment of both the measured and computed diffusion data in hcp Mg was performed using the above holistic approach to yield the most comprehensive open Mg mobility database to date, comprising 23 elements (Mg, Ag, Al, Be, Ca, Cd, Ce, Cu, Fe, Ga, Gd, In, La, Li, Mn, Nd, Ni, Pu, Sb, Sn, U, Y, Zn). This more reliable mobility database will contribute to future development of advanced Mg alloys. The holistic approach developed in this study will be very beneficial to the future establishment of reliable mobility databases for other alloy systems as well.

36 MATERIALS SCIENCE↗

Bringing chemical structures to life with augmented reality, machine learning, and quantum chemistry

Visualizing 3D molecular structures is crucial to understanding and predicting their chemical behavior. However, static 2D hand-drawn skeletal structures remain the preferred method of chemical communication. Here, we combine cutting-edge technologies in augmented reality (AR), machine learning, and computational chemistry to develop MolAR, an open-source mobile application for visualizing molecules in AR directly from their hand-drawn chemical structures. Users can also visualize any molecule or protein directly from its name or protein data bank ID and compute chemical properties in real time via quantum chemistry cloud computing. MolAR provides an easily accessible platform for the scientific community to visualize and interact with 3D molecular structures in an immersive and engaging way.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Revisiting excitation gaps in the fractional quantum Hall effect

Recent systematic measurements of the quantum well width dependence of the excitation gaps of fractional quantum Hall states in high mobility samples open the possibility of a better quantitative understanding of this important issue. Here we present what we believe to be accurate theoretical gaps including the effects of finite width and Landau level (LL) mixing. While theory captures the width dependence, there still remains a deviation between the calculated and the measured gaps, presumably caused by disorder. It is customary to model the experimental gaps of the n/(2n ± 1) states as Δ n/(2n+1) = Ce 2 /[(2n ± 1)ϵl]-Γ, where ϵ is the dielectric constant of the background semiconductor and l is the magnetic length; the first term is interpreted as the cyclotron energy of composite fermions and Γ as a disorder-induced broadening of composite-fermion LLs. Fitting the gaps for various fractional quantum Hall states, we find that Γ can be nonzero even in the absence of disorder.

36 MATERIALS SCIENCE↗

Label Assist: Personalized Travel Models for Longitudinal Data Collection

Understanding travel behavior is crucial to transportation decarbonization. OpenPATH is an open-source mobility platform which collects and analyzes human travel behavior at the individual level. The mobile application passively senses trips and prompts users to label them. However, users find the labeling process burdensome; less than half the trips are typically labeled, making much of the data unusable in aggregate analyses of mobility patterns. Prior work has addressed the response fatigue challenge through automated mode inference using sensor data, but sensors cannot capture all aspects of travel behavior. We explore an alternative approach in which we leverage prior user input to predict travel choices in novel trips. We first explore trip clustering methods and develop a novel two-step pipeline using DBSCAN and SVMs to extract realistic geospatial clusters. We then propose two strategies to predict trip labels: (i) clustering trips and extrapolating labels for similar trips, and (ii) random forest classification. The random forest approach is able to achieve - $70-80% accuracy (purpose: 72%, mode: 79%, replaced mode: 81%). These novel approaches to trip classification allow us to increase the rate of user labeling by suggesting predicted labels to be verified by the user. Unlabeled trips can also contribute to aggregate analyses, using label predictions and their associated confidences as a substitute. While there exist other travel survey apps with the ability to infer travel choices, to our knowledge, this is the first paper to describe such a supervised system and rigorously evaluate it.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

Integrated Methane Monitoring Platform Design

This report presents design plans for integrated methane monitoring platforms for the oil and gas sector, which include satellites, aircrafts, drones, mobile platforms, open-path systems, sensor networks, LDAR techniques, and other systems.

03 NATURAL GAS↗

Open-Source Data for MAC-POSTS: Mobility Data Analytics Center - Prediction, Optimization, and Simulation Toolkit for Transportation Systems

MAC-POSTS (Mobility Data Analytics Center - Prediction, Optimization, and Simulation toolkit for Transportation Systems) is a toolkit for dynamic transportation network modeling. Developed by the Mobility Data Analytics Center (MAC) at Carnegie Mellon University, this package implements many classic dynamic transportation network models, as well as new models proposed by MAC members. It has served as one building block for many other models and research projects. As such, this package used to be treated as an internal research project of the MAC lab, and admittedly, the code base is messy, and the interface is hard to use. However, we are working hard to make it a generally usable and useful toolkit for dynamic transportation network modeling. We would really appreciate any feedback, comments, suggestions, or criticisms.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Impact of dopant-induced band tails on optical spectra, charge carrier transport, and dynamics in single-crystal CdTe

Abstract Cadmium telluride (CdTe) semiconductors are used in thin-film photovoltaics, detectors, and other optoelectronic applications. For all technologies, higher efficiency and sensitivity are achieved with reduced charge carrier recombination. In this study, we use state-of-the-art CdTe single crystals and electro-optical measurements to develop a detailed understanding of recombination rate dependence on excitation and temperature in CdTe. We study recombination and carrier dynamics in high-resistivity (undoped) and arsenic (As)-doped CdTe by employing absorption, the Hall effect, time-resolved photoluminescence, and pump-probe in the 80–600 K temperature range. We report extraordinarily long lifetimes (30 µs) at low temperatures in bulk undoped CdTe. Temperature dependencies of carrier density and mobility reveal ionization of the main acceptors and donors as well as dominant scattering by ionized impurities. We also distinguish different recombination defects. In particular, shallow As Te and deep V Cd −As Cd acceptors were responsible for p-type conductivity. AX donors were responsible for electron capture, while nonradiative recombination centers (V Cd −As Te , As 2 precipitates), and native defects (V Cd −Te Cd ) were found to be dominant in p-type and n-type CdTe, respectively. Bimolecular and surface recombination rate temperature dependencies were also revealed, with bimolecular coefficient T −3/2 temperature dependence and 170 meV effective surface barrier, leading to an increase in surface recombination velocity at high temperatures and excitations. The results of this study allowed us to conclude that enhanced crucible rotation growth of As-doped CdTe is advantageous to As activation, leading to longer lifetimes and larger mobilities and open-circuit voltages due to lower absorption and trapping.

36 MATERIALS SCIENCE↗

OpenPATH and Itinerum Integration: A Case Study of Merging Open-Source Projects: Preprint

Throughout the transportation sector, multiple mobility tracking platforms have been developed independently, in parallel, with similar use cases and infrastructure. Maintaining such platforms on an individual level can result in duplicated effort. Innovation within the field could be slowed by the limited resource of people working on extremely similar projects. We provide a case study in how such platforms can be combined with low effort and provide an example in the mobility domain of what the resulting integration points, modules and ownership may look like. OpenPATH (formerly e-mission) and Itinerum are two examples of similar independently developed human mobility tracking platforms that extend beyond standard traffic data collection. Due to the open source nature of the projects, members from both teams decided to merge the functionality, thereby only hosting a single data collection process and limiting maintenance of separate intake platforms. On the front-end, specific questionnaire functionality from Itinerum, mainly the ability to display and return questions and results focused on sociodemographic attributes, was integrated into the OpenPATH user interface. On the back-end, an export pipeline stage was created to transport collected data back to the Itinerum database. Upon completion, the OpenPATH application retained its original functionality while adding the ability to export data for future data sharing and creating an avenue to incorporate Itinerum hosted questions and answers. Itinerum benefits from the rich feature set and infrastructure of OpenPATH without losing needed elements such as the questionnaire component. This case study, within the transportation sector, illustrates the various configurations in which open source software can be developed, maintained and deployed.

ADVANCED PROPULSION SYSTEMS↗

mzapy : An Open-Source Python Library Enabling Efficient Extraction and Processing of Ion Mobility Spectrometry-Mass Spectrometry Data in the MZA File Format

We have recently reported MZA, a new and simple mass spectrometry data structure based on the broadly supported HDF5 format and created to facilitate software development. While this format is inherently supportive of application development, the availability of a core library with standard mass spectrometry utilities greatly facilitates fast software development. Here, we present a Python library, mzapy, for efficient extraction and processing of mass spectrometry data in the MZA format. In addition to raw data extraction, mzapy contains supporting utilities enabling tasks including calibration, signal processing, peak finding, and generating plots. Being implemented in pure Python with minimal and largely standardized dependencies makes mzapy uniquely suited to application development in the multi-omics domain. The free and open source mzapy is built with extensibility in mind, and future development will support cloud computing and artificial intelligence/machine learning applications. The software source code is freely available at https://github.com/PNNL-m-q/mzapy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Volumetric Additive Manufacturing of Dicyclopentadiene by Solid‐State Photopolymerization

Polymerization in the solid state is generally infeasible due to restrictions on mobility. However, in this work, the solid-state photopolymerization of crystalline dicyclopentadiene is demonstrated via photoinitiated ring-opening metathesis polymerization. The source of mobility in the solid state is attributed to the plastic crystal nature of dicyclopentadiene, which yields local short-range mobility due to orientational degrees of freedom. Polymerization in the solid state enables photopatterning, volumetric additive manufacturing of free-standing structures, and fabrication with embedded components. Solid-state photopolymerization of dicyclopentadiene offers a new paradigm for advanced and freeform fabrication of high-performance thermosets.

additive manufacturing↗

Mobility Energy Productivity and Equity: E-Bike Impacts for Low-Income Essential Workers in Denver

New mobility technologies such as electrified and shared mobility, combined with polices and incentive programs, are emerging to help address sustainability and equity issues in transportation planning. However, it can be difficult to understand the impacts of novel mobility trends and emerging modes on energy-efficient access. This is owing to a lack of (1) open-source tools enabling rapid data collection, and (2) open-source metrics that consider multimodal, multiactivity access and mobility within the contexts of sustainability and equity. Here, this paper addresses the topic of improving evaluation of transportation modes and incentive programs by integrating an open-source platform for tracking human travel data—the Open Platform for Agile Trip Heuristics (OpenPATH)—with a mobility metric that quantifies the efficiency of a region’s transportation system: Mobility Energy Productivity (MEP). Integration is demonstrated in the context of pilot programs in Colorado, where low-income essential workers were provided with electric bikes (e-bikes). OpenPATH-informed MEP calculations showed that several locations in downtown Denver provided comparable time-, cost-, and energy-efficient access to opportunities using e-bikes compared with driving. Additionally, providing e-bikes to low-income essential workers was found to be meaningful, as they utilized e-bikes the most to commute, despite driving still being their most utilized mode and the mode with highest MEP scores in Denver. We show how data collected from open-source tools coupled with robust metrics such as MEP can help evaluate the impacts of emerging mobility options. This could support developing policies to incentivize novel modes to achieve greater levels of sustainable, equitable, and efficient access.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Assessing the impact of human mobility to predict regional excess death in Ecuador

Abstract COVID-19 outbreaks have had high mortality in low- and middle-income countries such as Ecuador. Human mobility is an important factor influencing the spread of diseases possibly leading to a high burden of disease at the country level. Drastic control measures, such as complete lockdown, are effective epidemic controls, yet in practice one hopes that a partial shutdown would suffice. It is an open problem to determine how much mobility can be allowed while controlling an outbreak. In this paper, we use statistical models to relate human mobility to the excess death in Ecuador while controlling for demographic factors. The mobility index provided by GRANDATA, based on mobile phone users, represents the change of number of out-of-home events with respect to a benchmark date (March 2nd, 2020). The study confirms the global trend that more men are dying than expected compared to women, and that people under 30 show less deaths than expected, particularly individuals younger than 20 with a death rate reduction between 22 and 27%. The weekly median mobility time series shows a sharp decrease in human mobility immediately after a national lockdown was declared on March 17, 2020 and a progressive increase towards the pre-lockdown level within two months. Relating median mobility to excess deaths shows a lag in its effect: first, a decrease in mobility in the previous two to three weeks decreases excess death and, more novel, we found an increase of mobility variability four weeks prior increases the number of excess deaths.

59 BASIC BIOLOGICAL SCIENCES↗

Data Needs for Modeling Low-Temperature Non-Equilibrium Plasmas: The LXCat Project, History, Perspectives and a Tutorial

Technologies based on non-equilibrium, low-temperature plasmas are ubiquitous in today’s society. Plasma modeling plays an essential role in their understanding, development and optimization. An accurate description of electron and ion collisions with neutrals and their transport is required to correctly describe plasma properties as a function of external parameters. LXCat is an open-access, web-based platform for storing, exchanging and manipulating data needed for modeling the electron and ion components of non-equilibrium, low-temperature plasmas. The data types supported by LXCat are electron- and ion-scattering cross-sections with neutrals (total and differential), interaction potentials, oscillator strengths, and electron- and ion-swarm/transport parameters. Online tools allow users to identify and compare the data through plotting routines, and use the data to generate swarm parameters and reaction rates with the integrated electron Boltzmann solver. In this review, the historical evolution of the project and some perspectives on its future are discussed together with a tutorial review for using data from LXCat.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Emerging mobile lidar technology to study boundary layer winds influenced by operating turbines

The development of a microjoule-class pulsed Doppler lidar and deployment of this compact system on mobile platforms such as aircraft, ships, or trucks have opened a new opportunity to characterize the dynamics of complex mesoscale wind flows. The PickUp-based Mobile Atmospheric Sounder (PUMAS) truck-based lidar system was recently used during the American Wake Experiment (AWAKEN) to assess the general structure of boundary layer (BL) wind and turbulence around wind turbines in central Oklahoma. Wind speed profiles averaged over PUMAS transects influenced by the operating turbines (waked flow) show a 1–2 m s −1 reduction compared to mean undisturbed (free flow) wind speed profiles. Spatial variability in wind speed was observed in time–height cross-sections at different distances from turbines. The wind speeds were about 9–12 m s −1 at 6 km distance compared to 5–7 m s −1 at the transects near the turbines. The PUMAS dataset from AWAKEN demonstrated the capability of the mobile Doppler lidar system to document spatial variability in wind flows at different distances from wind turbines and obtain quantitative estimates of wind speed reduction in the waked flow. The high-frequency, simultaneous measurements of the horizontal and vertical winds provide a new approach for characterizing dynamic processes critical for wind farm wake analyses.

17 WIND ENERGY↗