Search NASA⌕ Search

SEARCH · Search NASA

Results for “Mobile computing”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 307 records · Page 17

Exploring the relation between transonic dislocation glide and stacking fault width in FCC metals

Theory predicts limiting gliding velocities that dislocations cannot overcome. Computational and recent experiments have shown that these limiting velocities are soft barriers and dislocations can reach transonic speeds in high rate plastic deformation scenarios. In this paper we systematically examine the mobility of edge and screw dislocations in several face centered cubic (FCC) metals (Al, Au, Pt, and Ni) in the extreme large-applied-stress regime using molecular dynamics simulations. Our results show that edge dislocations are more likely to move at transonic velocities due to their high mobility and lower limiting velocity than screw dislocations. Importantly, among the considered FCC metals, the dislocation core structure determines the dislocation’s ability to reach transonic velocities. This is likely due to the variation in stacking fault width due to relativistic effects near the limiting velocities.

36 MATERIALS SCIENCE↗

Surrogate Modeling for Capacity Planning of Charging Station Equipped With Photovoltaic Panel and Hydropneumatic Energy Storage

Due to the promising potential for environmental sustainability, there has been a significant increase of electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEV) in the market. To support this increasing demand for EVs and PHEVs, challenges related to capacity planning and investment costs of public charging infrastructure must be addressed. Hence, in this paper, a capacity planning problem for charging stations is developed and aims to balance the current capital investment costs and future operational revenue. The charging station is assumed to be equipped with the solar photovoltaic (PV) panel and an energy storage system, which could be electric battery or recently invented hydropneumatic energy storage (ground-level integrated diverse energy storage (GLIDES)) system. A co-optimization model that minimizes investment and operation cost is established to determine optimal solution while considering capacity planning and following operations. EV mobility is modeled as an Erlang-loss system. Meanwhile, stochastic programming is adopted to capture uncertainties from solar radiation and charging demand of EV fleet. To provide a more general and computationally efficient model, main configuration parameters are sampled in design space and then fixed in solving the co-optimization model. Sampled parameters include EV charging slots number, PV area, capacity of energy storage system, and daily mean EV arrival number. Based on the sampled parameter combinations and its responses, black-box mappings are then constructed using surrogate models, which could provide insights for charging station placement in different practical situations. The effectiveness of the proposed surrogate modeling approach is demonstrated in numerical experiments. Here, the results indicate better profit advantage of GLIDES over battery system with the increased power capacity

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A step towards a holistic assessment of soil degradation in Europe: Coupling on-site erosion with sediment transfer and carbon fluxes

Highlights: • WaTEM/SEDEM was applied to simulate soil loss and deposition rates at European scale. • Our findings indicate that soil loss in the riverine systems is about 15% of RUSLE2015 estimates. • The estimated sediment yield in Europe totals 0.164 ± 0.013 Pg yr{sup −1}. • We estimate a SOC displacement by water erosion in Europe of 14.5 Tg yr{sup −1}. Soil degradation due to erosion is connected to two serious environmental impacts: (i) on-site soil loss and (ii) off-site effects of sediment transfer through the landscape. The potential impact of soil erosion processes on biogeochemical cycles has received increasing attention in the last two decades. Properly designed modelling assumptions on effective soil loss are a key pre-requisite to improve our understanding of the magnitude of nutrients that are mobilized through soil erosion and the resultant effects. The aim of this study is to quantify the potential spatial displacement and transport of soil sediments due to water erosion at European scale. We computed long-term averages of annual soil loss and deposition rates by means of the extensively tested spatially distributed WaTEM/SEDEM model. Our findings indicate that soil loss from Europe in the riverine systems is about 15% of the estimated gross on-site erosion. The estimated sediment yield totals 0.164 ± 0.013 Pg yr{sup −1} (which corresponds to 4.62 ± 0.37 Mg ha{sup −1} yr{sup −1} in the erosion area). The greatest amount of gross on-site erosion as well as soil loss to rivers occurs in the agricultural land (93.5%). By contrast, forestland and other semi-natural vegetation areas experience an overall surplus of sediments which is driven by a re-deposition of sediments eroded from agricultural land. Combining the predicted soil loss rates with the European soil organic carbon (SOC) stock, we estimate a SOC displacement by water erosion of 14.5 Tg yr{sup −1}. The SOC potentially transferred to the riverine system equals to 2.2 Tg yr{sup −1} (~15%). Integrated sediment delivery-biogeochemical models need to answer the question on how carbon mineralization during detachment and transport might be balanced or even off-set by carbon sequestration due to dynamic replacement and sediment burial.

54 ENVIRONMENTAL SCIENCES↗

Intermetallic phase formation in Al-Si-Zr alloys during hot isostatic pressing revealed by experiments and molecular dynamics

Understanding phase transformations at alloy interfaces is critical for the design of advanced structural materials. Here, in this study, we investigate the formation mechanisms of the Al 2 SiZr intermetallic phase in the Al-Si-Zr system under hot isostatic pressing (HIP) using molecular dynamics (MD) simulations and thermodynamic analysis. A unique aspect of our approach in MD involves the replacement of a disordered Al 2 SiZr stoichiometry with an ordered phase at the Al-Zr interface once HIP results in the desired Al 2 SiZr stoichiometry, allowing us to compute the total energetic cost of transformation by accounting for both formation energies and diffusion barriers. Diffusion coefficients and activation energies, extracted across a range of temperatures, reveal that HIP substantially enhances atomic mobility, creating favorable stoichiometry for phase evolution. Our results show that Al 2 SiZr phase formation is kinetically unfavorable at lower temperatures but becomes feasible when the thermodynamic driving energy surpass a critical energy threshold.

Roy, Ankit [Pacific Northwest National Laboratory ↗

Coupled Transport, Reactivity, and Mechanics in Fractured Shale Caprocks

Abstract Shales are low‐permeability caprocks that confine fluid, such as CO 2 , nuclear waste, and hydrogen, in storage formations. Stress‐induced fractures in shale caprocks provide pathways for fluid to leak and potentially contaminate fresh water aquifers. Fractured shales are also increasingly considered as resources for CO 2 sequestration, enhanced geothermal, and unconventional energy recovery. Injecting reactive fluids into shales introduces chemical disequilibrium, causing an onset of a series of dissolution, precipitation, and fines mobilization mechanisms. The reactions have rapid kinetics and significant impact on porosity and permeability; consequently, flow and storage properties of caprocks. While previous research has explored the separate effects of these reactions, this study aims to uncover their simultaneous occurrence and collective influence. This study unveils these highly coupled transport and reactivity mechanisms by tracking and visualizing the reaction‐induced alterations in the matrix, microcracks, and fractures of shales over time. We conducted brine injection experiments sequentially at pH 4 and 2 in a naturally fractured Wolfcamp shale sample while simultaneously imaging the dynamic processes using X‐ray computed tomography (CT). CT images are validated by finer resolution images obtained using micro‐CT and scanning electron microscopy. We also tracked the sample permeability and fluid chemistry using brine permeability and inductively coupled plasma mass spectrometry, respectively. Findings show that fluid primarily flowed through fractures, dissolving reactive minerals and mobilizing fines on fracture surfaces. Dissolution of fracture asperities under confining stress resulted in the closing of fractures. Clogging in narrow fracture pathways, caused by fines accumulation, diverted fluid flow into matrix pores.

58 GEOSCIENCES↗

Two-dimensional ruthenium boride: a Dirac nodal loop quantum electrocatalyst for efficient hydrogen evolution reaction

Catalysts with high carrier mobility, high activity, and an active basal plane have been highly sought for the hydrogen evolution reaction (HER). However, combining these advantages into one single material is a grand challenge. Herein, using first principles computations, we predicted that a two-dimensional (2D) Dirac nodal loop semimetal, namely the RuB 4 monolayer, is promising as a superior catalyst for the HER. Our systematic computations showed that the single layer RuB 4 is thermodynamically, dynamically, mechanically, and thermally stable and presents multiple Ru and B sites for the HER on the basal plane. The estimated Gibbs free energy for hydrogen adsorption at a Ru site is approaching zero (–8.8 meV), suggesting its excellent HER performance. The RuB 4 monolayer is a Dirac nodal loop semimetal with high Fermi velocities, which can accelerate charge transfer between catalysts and reaction intermediates. The RuB 4 monolayer is an auxetic material with an out-of-plane negative Poisson's ratio, implying its novel mechanical properties. Finally, this work provides an example of using a Dirac nodal loop semimetal for high-performance HER catalysts, which is a promising alternative to the known catalysts with trivial metallic properties.

30 DIRECT ENERGY CONVERSION↗

Surrogate Modeling for Capacity Planning of Charging Station Equipped with PV and Hydropneumatic Energy Storage

Due to the promising potential for environmental sustainability, there has been a significant increase of electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEV) in the market. To support this increasing demand for EVs and PHEVs, challenges related to capacity planning and investment costs of public charging infrastructure must be addressed. Hence, in this paper, a capacity planning problem for EV charging stations is developed and aims to balance current capital investment costs and future operational revenue. The charging station considered in this work is assumed to be equipped with solar photovoltaic panel (PV) and an energy storage system which could be electric battery or the recently invented hydro-pneumatic energy storage (GLIDES, Ground-Level Integrated Diverse Energy Storage) system. A co-optimization model that minimizes investment and operation cost is established to determine the global optimal solution while combining the capacity and operational decision making. The operational decision making considers EV mobility which is modeled as an Erlang-loss system. Meanwhile, stochastic programming is adopted to capture uncertainties from solar radiation and charging demand of the EV fleet. To provide a more general and computationally efficient model, main configuration parameters are sampled in the design space and then fixed in solving the co-optimization model. The model can be used to provide insights for charging station placement in different practical situations. The sampled parameters include: the total number of EV charging slots, the PV area, the maximum capacity of the energy storage system, and daily mean EV arrival number in the Erlang-loss system. Based on the sampled parameter combinations and its responses, black-box mappings are then constructed using surrogate models (RBF, Kriging etc). The effectiveness of proposed surrogate modeling approach is demonstrated in the numerical experiments.

Chen, Yang↗

Optical Particle Measurements during EPCAPE Field Campaign Report

This campaign requested the deployment of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) User Facility optical particle counter (OPC) at the first ARM Mobile Facility (AMF1) located at the Scripps Pier in La Jolla, California during the Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE). The addition of the OPC was requested for two reasons. (1) Close the gap between the scanning mobility particle sizer (SMPS) and aerodynamic particle sizer (APS) size distribution from the Aerosol Observing System (AOS) measurements. (2) Principal investigator Petters has been working with Tracking Aerosol Convection Interaction Experiment (TRACER) data to compute particle fluxes from Doppler lidar (Petters et al. 2024). Briefly, backscatter flux is obtained using the eddy covariance technique using the Doppler vertical velocity and attenuated backscatter. Building upon prior studies, we were able to relate backscatter to particle number concentration by calibrating the lidar retrievals against optical particle counter-measured ground-based aerosol size distribution and radiosonde-interpolated relative humidity at lidar sample height. Performing similar analysis was of interest to EPCAPE to better understand the emissions and vertical transport of large particles into the overlying stratus clouds. However, as stated above, this analysis requires an optical size distribution that covers the 0.3-30-μm-diameter size range. The OPC was deployed between 2023-04-14 and 2024-02-14. The deployment, data quality analysis, and data archiving was handled by the DOE ARM instrument mentor team without additional involvement by the principal investigator. Data quality was marked as “routine” for the majority of the campaign.

54 ENVIRONMENTAL SCIENCES↗

Dynamic Symmetry Breaking in Chiral Magnetic Systems

The Dzyaloshinskii–Moriya interaction (DMI) in magnetic systems stabilizes spin textures with preferred chirality, applicable to next-generation memory and computing architectures. In perpendicularly magnetized heavy-metal/ferromagnet films, the interfacial DMI originating from structural inversion asymmetry and strong spin-orbit coupling favors chiral Néel-type domain walls (DWs) whose energetics and mobility remain at issue. Thus, a new effect is characterized in which domains expand unidirectionally in response to a combination of out-of-plane and in-plane magnetic fields, with the growth direction controlled by the in-plane field strength. These growth directionalities and symmetries with applied fields cannot be understood from static treatments alone. The authors theoretically demonstrate that perpendicular field torques stabilize steady-state magnetization profiles highly asymmetric in elastic energy, resulting in a dynamic symmetry breaking consistent with the experimental findings. This phenomenon sheds light on the mechanisms governing the dynamics of Néel-type DWs and expands the utility of field-driven DW motion to probe and control chiral DWs.

36 MATERIALS SCIENCE↗

Enhancing Biopolyester Backbone Rigidity with an Asymmetric Furanic Monomer

Biobased furanic polyesters can exhibit performance advantages over petroleum-derived polyesters, primarily due to their rigid furan-containing backbones. Herein, we develop two strategies to polymerize methyl 5-hydroxymethyl furanoate to poly(5-hydroxymethyl furanoate) (PHMF), a furan-based polyester with even greater backbone rigidity than poly(ethylene furanoate). Thermal, spectroscopic, and computational investigations of PHMF alongside analogous furan-based and phenyl-based polyesters suggest that the high furan content of PHMF leads to its high glass transition temperature, slow crystallization kinetics, and low amorphous mobility. Molecular dynamics simulations suggest that while the backbone of PHMF is exceptionally rigid, its amorphous phase is denser than its phenyl analog due to noncovalent interchain interactions. Together, these results highlight how asymmetric furan-based monomers can modulate key properties in biobased polyesters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

In silico analyses of diversity and dissemination of antimicrobial resistance genes and mobile genetics elements, for plasmids of enteric pathogens

The antimicrobial resistance (AMR) mobilome plays a key role in the dissemination of resistance genes encoded by mobile genetics elements (MGEs) including plasmids, transposons (Tns), and insertion sequences (ISs). These MGEs contribute to the dissemination of multidrug resistance (MDR) in enteric bacterial pathogens which have been considered as a global public health risk. To further understand the diversity and distribution of AMR genes and MGEs across different plasmid types, we utilized multiple sequence-based computational approaches to evaluate AMR-associated plasmid genetics. A collection of 1,309 complete plasmid sequences from Gammaproteobacterial species, including 100 plasmids from each of the following 14 incompatibility (Inc) types: A/C, BO, FIA, FIB, FIC, FIIA, HI1, HI2, I1, K, M, N, P except W, where only 9 sequences were available, was extracted from the National Center for Biotechnology Information (NCBI) GenBank database using BLAST tools. The extracted FASTA files were analyzed using the AMRFinderPlus web-based tools to detect antimicrobial, disinfectant, biocide, and heavy metal resistance genes and ISFinder to identify IS/Tn MGEs within the plasmid sequences. In silico prediction based on plasmid replicon types showed that the resistance genes were diverse among plasmids, yet multiple genes were widely distributed across the plasmids from enteric bacterial species. These findings provide insights into the diversity of resistance genes and that MGEs mediate potential transmission of these genes across multiple plasmid replicon types. This notion was supported by the observation that many IS/Tn MGEs and resistance genes known to be associated with them were common across multiple different plasmid types. Our results provide critical insights about how the diverse population of resistance genes that are carried by the different plasmid types can allow for the dissemination of AMR across enteric bacteria. The results also highlight the value of computational-based approaches and in silico analyses for the assessment of AMR and MGEs, which are important elements of molecular epidemiology and public health outcomes.

59 BASIC BIOLOGICAL SCIENCES↗

Combined Mesonet and Tracker

Title: Combined Mesonet and Trackers (UNL Mobile Mesonets) Authors University of Nebraska PI: Adam Houston, UNL Professor (ahouston2@unl.edu) Mailing Address: 126 Bessey Hall P.O. Box 880340 Lincoln, NE 68588-0340 CoMeT Overview The University of Nebraska-Lincoln operates three Combined Mesonet and Tracker (CoMeTs). CoMeTs are Ford Explorers (model years 2015, 2017, and 2019) with forward-mounted suites of meteorological sensors and dual moonroofs, combining the capability of a mobile mesonet to collect near-surface observations with the capability of an unmanned aircraft systems (UAS) tracker vehicle, which enables an observer in the second row of seats to see the aircraft and maintain compliance with Federal Aviation Administration policies on UAS operation. The CoMeTs collect observations of slow temperature and humidity at ~2 m above ground level (AGL) using a Vaisala HMP155A, fast temperature at ~2 m AGL using a Campbell Scientific 109SS-L thermistor, pressure at ~2.5 m AGL using a Vaisala PTB210, wind speed and direction at ~3.25 m AGL using an R.M. Young 05103 propeller anemometer, and vehicle heading using a KVH Industries C-100 fluxgate compass (Barbieri et al. 2019). The HMP155A and 109SS-L thermistor are shielded and aspirated within a U-tube (Waugh and Frederickson 2010; Houston et al. 2016). This list of sensors is also included in the CoMeT data file metadata. Manufacturer specifications for these instruments are given in Table 1 of Hanft and Houston (2018). The reported measured quantities are summarized below.CoMeT-3 was funded through an equipment allocation included in the NSF TORUS award (AGS-1824649). Instrument Description The specific sensors included on each CoMeT are summarized in the table at the end of this section. In general each CoMeT collects observations of slow temperature and humidity at ~2 m above ground level (AGL) using a Vaisala HMP155, fast temperature at ~2 m AGL using a Campbell Scientific 109SS-L thermistor, pressure at ~2.5 m AGL using a Vaisala PTB210 barometer with a Gill pressure port, wind speed and direction at ~3.25 m AGL using an R.M. Young 05103 propeller anemometer, position using a Garmin 19x HVS receiver, and vehicle heading using a KVH Industries C-100 fluxgate compass. The HMP155 and 109SS are shielded and aspirated within a U-tube (Waugh and Frederickson 2010; Houston et al. 2016). Fast temperature and corrected RH measurements (using sensors housed within the U-tube) have a time constant of 10-12 s based on data collected across a temperature and RH shock during the CLOUD-MAP 2017 calibration/validation tests on June 26, 2017. Vehicle speed was < 10 kts for this test. CoMeT-1 CoMeT-2 CoMeT-3 Slow Temperature Slow RH Vaisala HMP155A-L20-PT Part #: 22280-7 Vaisala HMP155E Part #: E1AA11A0B1A1A0A Vaisala HMP155E Part #: E1AA11A0B1A1A0A Fast temperature Campbell Scientific 109SS-L20-PT Part #: 21448-3 Campbell Scientific 109SS-L12-PW Part #: 21448-109 Campbell Scientific 109SS-L12-PW Part #: 21448-150 Pressure Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Wind RM Young 05103-L20-PT Part #: 18435-310 RM Young 05103-L20-PW Part #: 18435-244 RM Young 05103-L20-PW Part #: 18435-244 GPS Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Compass KVH C-100 Part #: 01-0177-15 KVH C-100 Part #: 01-0177-15 KVH C-100 Part #: 01-0177-15 Logger Campbell Scientific CR6-NA-XT-SW Part #: 28385-9 Campbell Scientific CR6-WIFI-XT-SW Part #: 28385-6 Campbell Scientific CR6-WIFI-XT-SW Part #: 28385-6 Data Collection and Real-Time Processing The reported measured quantities are summarized in the table below. Quantity Units Source Epoch time Seconds GPS Latitude and longitude Degrees GPS Altitude m GPS Pressure hPa PTB210 Temperature (fast) deg C 109SS-L Temperature (slow) deg C HMP155 RH (slow) % HMP155 Vehicle speed m/s GPS Vehicle heading deg C-100 and GPS In addition to the measured variables, several derived variables are calculated. Corrected/fast relative humidity (%) Relative humidity is adjusted to the fast temperature following Richardson et al. (1998) and Houston et al. (2016). Water vapor mixing ratio (g/kg) Dew point temperature (&deg;C) Potential temperature (Kelvin) Virtual potential temperature (Kelvin) Equivalent potential temperature (Kelvin) Regular intercomparisons between all three CoMeTs were performed during TORUS 2019. Comparisons were also conducted between CoMeT-1 and CoMeT-2 during LAPSE-RATE (2018) on 14 July. In these intercomparisons, the vehicles were parked adjacent to each other aligned perpendicular to (and facing into) the wind. To minimize engine heating effects, intercomparisons were only conducted when the wind speed was >10 kts. Data Format Original data files for each deployment are saved as text files and then converted to NetCDF. NetCDF versions have units that are CF compliant and may not match the original units in the txt files. The naming convention for the NetCDF files is as follows: UNL.CoMeT3.{deployment date YYYYMMDD}.{start time of observation collection in UTC HHMM}.L2.{post-processing codes}.cdf example: UNL.CoMeT3.20190627.1931.L2.g1.f1.cdf Post-processing codes are included to track modifications to the raw data. These codes are closely connected to error flags associated with each record. Each letter corresponds to a particular instrument: g: GPS p: Barometer tf: Fast temperature ts: Slow temperature rh: Relative humidity f: Compass w: Wind monitor a: All instruments Each number corresponds to a particular post-processing action described more below. Measured and derived variables are included in the following table. Variable Heading Standard Name Units time Time seconds since 00:00:00, 01-01-1970 Alt Altitude meters lat Latitude degrees north lon Longitude degrees east fast_temp Air Temperature kelvin slow_temp Air Temperature kelvin pressure Air Pressure pascals logger_RH Relative Humidity percent calc_corr_RH Relative Humidity percent wind_speed Wind Speed meters per second wind_dir Wind From Direction degrees vehicle_dir Vehicle Direction degrees dewpoint Dew Point Temperature kelvin mixing_ratio Humidity Mixing Ratio g/g theta Air Potential Temperature kelvin theta_v Virtual Potential Temperature kelvin theta_e Equivalent Potential Temperature Kelvin error_flag The error_flag variable is a string that matches the post-processing codes listed above. All instruments will have an associated code, but will have a &ldquo;0&rdquo; if the datum is unchanged from the initial processed value. Error Codes The following table summarizes the error codes for data collected before 2020: Error Code Relevant CoMeT Description g1 1,2,3 Exact correction. GPS position and time reprocessed from raw data g2 1 As far as we can tell this is an exact correction to an error in the GPS time. During the correct time periods the time suddenly went backwards ~250s and stayed at this offset for 750s when it corrected itself. The offset was applied to the &ldquo;time warp&rdquo; period. p1 2 Approximate correction. Hole in the pressure tube connecting the pressure port to the barometer. Resulted in erroneously low air pressure measurements when the vehicle was in motion. Derived variables recalculated (dew point temperature [e depends on qv and p], water vapor mixing ratio, potential temperature, virtual potential temperature, equivalent potential temperature) a1 3 Exact correction. Missing data reprocessed from raw data a2 1 Bug fix to bias correction for ts1, ts2, and rh1: water vapor mixing ratio was off by a factor of 10 and virtual potential temperature was wrong because of this. f1 3 No correction, missing data. Fluxgate compass inoperable. Wind speed and direction calculated using GPS-derived vehicle heading instead. rh1 1 Approximate correction. Constant bias of +1.7% removed from relative humidity. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) ts1 1 Approximate correction. Constant bias of +0.6 K removed from slow temperature. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) ts2 1 Approximate correction. Constant bias of +1.0 K removed. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) References Bolton, D., 1980: The Computation of Equivalent Potential Temperature. Mon. Wea. Rev., 108, 1046&ndash;1053, https://doi.org/10.1175/1520-0493(1980)108<1046:TCOEPT>2.0.CO;2. Hanft, W., and A. L. Houston, 2018: An Observational and Modeling Study of Mesoscale Air Masses with High Theta-E. Mon. Wea. Rev., 146, 2503&ndash;2524, https://doi.org/10.1175/MWR-D-17-0389.1.Wexler Houston, A. L., R. J. Laurence III, T. W. Nichols, S. Waugh, B. Argrow, and C. L. Ziegler, 2016: Intercomparison of unmanned aircraft-borne and mobile mesonet atmospheric sensors. Journal of Atmospheric and Oceanic Technology. 33, 1569-1582, doi: 10.1175/JTECH-D-15-0178.1. Lowe, P. R., 1977: An Approximating Polynomial for the Computation of Saturation Vapor Pressure. J. Applied Meteorology, 16, 100&ndash;103. Richardson, S. J., S. E. Frederickson, F. V. Brock, and J. A. Brotzge, 1998: Combination temperature and relative humidity probes: Avoiding large air temperature errors and associated relative humidity errors. Preprints, 10th Symp. On Meteorological Observations and Instrumentation, Phoenix, AZ, Amer. Meteor. Soc., 278&ndash;283. Waugh, S., and S. E. Frederickson, 2010: An improved aspirated temperature system for mobile meteorological observations, especially in severe weather. 25th Conf. on Severe Local Storms, Denver, CO, Amer. Meteor. Soc., P5.2. [Available online at https://ams.confex.com/ams/25SLS/techprogram/paper_176205.htm.]

54 ENVIRONMENTAL SCIENCES↗

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↗

Environmental Contributions to Proton Sharing in Protein Low-Barrier Hydrogen Bonds

Hydrogen bonds (H-bonds) are central to biomolecular structure and dynamics. Although H-bonds are typically characterized by well-defined proton positions, proton delocalization has been proposed to play a role in facilitating enzyme catalysis and allostery in some systems. Experimentally locating protons is difficult, hampering the study of proton mobility in H-bonds. We used neutron crystallography, atomic resolution X-ray bond length analysis, and large quantum mechanics/molecular mechanics-Born–Oppenheimer molecular dynamics (QM/MM-BOMD) simulations to comprehensively characterize the shared proton/deuteron in a Glu–Asp low-barrier hydrogen bond (LBHB) in the bacterial protein YajL that is a conventional H-bond in the homologous disease-associated human protein DJ-1. X-ray bond length analysis of protiated and perdeuterated DJ-1 and YajL shows no significant effect of deuteron substitution on these carboxylic acid-carboxylate H-bonds but does reveal an effect at the active site glutamic acid near a cysteine thiolate. Residues in an H-bonded network that might favor LBHB formation in YajL were interrogated by the mutation of homologous residues in DJ-1. A distal DJ-1 substitution increases proton delocalization in the Glu–Asp H-bond, demonstrating that mutations within extended H-bond networks can modulate proton transfer barriers in carboxylic acid-carboxylate H-bonds. In addition, proton mobility in the H-bond is correlated with dimer-spanning motions in the QM/MM-BOMD simulations of YajL and DJ-1. Our results show that proton delocalization can be tuned using combined bioinformatic, structural, and computational information, opening the possibility of using engineered proton delocalization as a probe of H-bonding environments and as a tool to test hypotheses about LBHB function.

Lin, Jiusheng [University of Nebraska, Lincoln, NE↗

Simple Approximation for the Ideal Reference State of Gases Adsorbed on Solid-State Surfaces

Reference states are useful as models for facilitating calculations of equilibrium constants, and they may also serve as standard states that are convenient for organizing and tabulating thermodynamic data; however, standard state conventions and appropriate reference states for adsorbed species have received less attention than those for pure substances and solutes. Here, we compare seven choices of reference states for calculations of equilibrium constants and transition state theory rate constants for flat surfaces, in particular (1) an ideal 2D harmonic oscillator, (2) an ideal rigid-molecule harmonic oscillator, (3) an ideal 2D harmonic oscillator with separable surface modes, (4) a 2D ideal gas, (5) an ideal 2D hindered translator, (6) an ideal 2D hindered translator with lowest-order barriers, and (7) a simple ideal 2D hindered translator proposed in this work. The advantage of models 5–7 is that they can treat both mobile and localized adsorbates in a consistent way, whereas models 1–3 are only appropriate for localized adsorbates, and model 4 is only appropriate for a freely translating adsorbate. Furthermore, models 6 and 7 reduce the computational cost without the user having to calculate barrier heights for diffusion. An advantage of the simple ideal 2D hindered translator is that it has a physical high-temperature limit. We also propose a reference state for nonflat surfaces. Here, the user is encouraged to choose a reference state based on the appropriateness of the model and the practicality of the calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

New Orthophoto Generation Strategies from UAV and Ground Remote Sensing Platforms for High-Throughput Phenotyping

Remote sensing platforms have become an effective data acquisition tool for digital agriculture. Imaging sensors onboard unmanned aerial vehicles (UAVs) and tractors are providing unprecedented high-geometric-resolution data for several crop phenotyping activities (e.g., canopy cover estimation, plant localization, and flowering date identification). Among potential products, orthophotos play an important role in agricultural management. Traditional orthophoto generation strategies suffer from several artifacts (e.g., double mapping, excessive pixilation, and seamline distortions). The above problems are more pronounced when dealing with mid- to late-season imagery, which is often used for establishing flowering date (e.g., tassel and panicle detection for maize and sorghum crops, respectively). In response to these challenges, this paper introduces new strategies for generating orthophotos that are conducive to the straightforward detection of tassels and panicles. The orthophoto generation strategies are valid for both frame and push-broom imaging systems. The target function of these strategies is striking a balance between the improved visual appearance of tassels/panicles and their geolocation accuracy. The new strategies are based on generating a smooth digital surface model (DSM) that maintains the geolocation quality along the plant rows while reducing double mapping and pixilation artifacts. Moreover, seamline control strategies are applied to avoid having seamline distortions at locations where the tassels and panicles are expected. The quality of generated orthophotos is evaluated through visual inspection as well as quantitative assessment of the degree of similarity between the generated orthophotos and original images. Several experimental results from both UAV and ground platforms show that the proposed strategies do improve the visual quality of derived orthophotos while maintaining the geolocation accuracy at tassel/panicle locations.

54 ENVIRONMENTAL SCIENCES↗

ASSERT FY16 Analysis of Feedstock Companion Markets

Meeting Co-Optima biofuel production targets will require large quantities of mobilized biomass feedstock. Mobilization is of key importance as there is an abundance of biomass resources, yet little is available for purchase, let alone at desired quantity and quality levels needed for a continuous operation, e.g., a biorefinery. Therefore Co-Optima research includes outlining a path towards feedstock production at scale by understanding routes to mobilizing large quantities of biomass feedstock. Continuing along the vertically-integrated path that pioneer cellulosic biorefineries have taken will constrain the bioenergy industry to high biomass yield areas, limiting its ability to reach biofuel production at scale. To advance the cellulosic biofuels industry, a separation between feedstock supply and conversion is necessary. Thus, in contrast to the vertically integrated supply chain, two industries are required: a feedstock industry and a conversion industry. The split is beneficial for growers and feedstock processers as they are able to sell into multiple markets. That is, depots that produce value-add feedstock intermediates that are fully fungible in both the biofuels refining and other, so-called companion markets. As the biofuel industry is currently too small to leverage significant investment in up-stream infrastructure build-up, it requires an established (companion) market to secure demand, which de-risks potential investments and makes a build-up of processing and other logistics infrastructure more likely. A common concern to this theory however is that more demand by other markets could present a disadvantage for biofuels production as resource competition may increase prices leading to reduced availability of low-cost feedstock for biorefineries. To analyze the dynamics across multiple markets vying for the same resources, particularly the potential effects on resource price and distribution, the Companion Market Model (CMM) has been developed in this task by experts in feedstock supply chain analysis, market economics, and System Dynamics from the Idaho National Laboratory and MindsEye Computing.

09 BIOMASS FUELS↗