Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Micro”

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 937 records · Page 52

CPC data from TAMU TRACER campaign in the Houston, TX region from July to September 2022

During TRACER, the Texas A&M Rapid Onsite Atmospheric Measurements Van (ROAM-V) was deployed to capture airmasses behind (maritime) and ahead (continental) of the passage of the sea-breeze front through Houston. On select sampling days, ROAM-V sampled in the morning/mid-day on the coast and then transited to a second inland site for the afternoon/evening. The suite of instruments deployed on ROAM-V included a Condensation Particle Counter (CPC; GRIMM Model 5.403 CPC), Scanning Mobility Particle Sizer (SMPS; TSI 3750 detector, TSI 3082 classifier, TSI 3088 neutralizer, TSI 3081A Differential Mobility Analyzer), Cloud Condensation Nuclei counter (Droplet Measurement Technologies CCN Counter), micro pulse lidar (Droplet Measurement Technologies Micro Pulse LiDAR (miniMPL)), and a Davis Rotating Uniform size-cut Monitor (DRUM; DRUMAir 4-DRUM). Before sampling at each location, the latitude and longitude were recorded using the GPS on the phone application “My Altitude”. Onboard the ROAM-V, aerosol samples are drawn through a shared isokinetic inlet at a flow rate ranging from 3.5 to 7.0 LPM. A portion of this flow is directed through a cyclone impactor (Brechtel, Inc. Model SCC 0.732) and 0.3 LPM is directed to the CPC. To correct the data for particle losses, we used a two-step method. First, the measured SMPS size distributions were used to calculate total particle loss through the inlet for every SMPS scan at a single deployment location. Second, the CPC data was corrected for particle losses using the average of the total losses per scan. This calculation was done separately for each deployment location due to changes in the measured size distributions between locations. Particle loss from diffusion (based on Kesten, 1991 and Gormley, 1949), inertial impaction in 90-degree bends (based on Aerosol Measurement, 2011 and Crane, 1977), and cyclone impactor efficiency (based on Dirgo, 1985) were included in the loss calculation. When the SMPS was not sampling at a location (in the case of an instrument malfunction or operator error), the reported CPC data was corrected with an average of the total losses for the entire campaign at the specified deployment location (e.g., if we needed to correct Galveston data, then the average of all calculated losses at Galveston was taken). These flatline corrections were used for all data on 22/07/13, 22/07/20, 22/07/22, and the data from Galveston on 22/08/09. An additional flatline correction of 14% was applied to all CPC data based on laboratory calibration prior to and after the campaign. In laboratory calibrations, we identified that for the same sample of air the field CPC (GRIMM Model 5.403 CPC) undercounted the total concentration of particles by 14% compared to the ground truth laboratory CPC (TSI Model 3750). This data was collected for ARM Field Campaign AFC07055 and supported by DOE ASR grant DE-SC0021047. For any further questions, please feel free to contact the instrument PI, Sarah D. Brooks, sbrooks@tamu.edu. Kesten et. al. Calibration of a TSI Model 3025 Ultrafine Condensation Particle Counter. Aerosol Science and Technology, 15:2, 107-111, 1991. Gormley et. al. Diffusion from a Stream Flowing through a Cylindrical Tube. Proceedings of the Royal Irish Academy, Vol 52, 163-169, 1948. Aerosol Measurement: Principles, Techniques, and Applications, Third Edition. John Wiley & Sons, Inc, 2011. Crane et. al. Inertial Deposition of Particles in a Bent Pipe. Journal of Aerosol Science, Vol 8, 161-170, 1977. Dirgo et. al. Cyclone Collection Efficiency: Comparison of Experimental Results with Theoretical Predictions. Aerosol Science and Technology, 4:4, 401-415, 1985.

54 ENVIRONMENTAL SCIENCES↗

CCN data from TAMU TRACER campaign in the Houston TX region from July to September 2022

During TRACER, the Texas A&M Rapid Onsite Atmospheric Measurements Van (ROAM-V) was deployed to capture airmasses behind (maritime) and ahead (continental) of the passage of the sea-breeze front through Houston. On select sampling days, ROAM-V sampled in the morning/mid-day on the coast and then transited to a second inland site for the afternoon/evening. The suite of instruments deployed on ROAM-V included a Condensation Particle Counter (CPC; GRIMM Model 5.403 CPC), Scanning Mobility Particle Sizer (SMPS; TSI 3750 detector, TSI 3082 classifier, TSI 3088 neutralizer, TSI 3081A Differential Mobility Analyzer), Cloud Condensation Nuclei counter (Droplet Measurement Technologies CCN Counter), micro pulse lidar (Droplet Measurement Technologies Micro Pulse LiDAR (miniMPL)), and a Davis Rotating Uniform size-cut Monitor (DRUM; DRUMAir 4-DRUM). Before sampling at each location, the latitude and longitude were recorded using the GPS on the phone application “My Altitude”. Onboard the ROAM-V, aerosol samples are drawn through a shared isokinetic inlet at a flow rate ranging from 3.5 to 7.0 LPM. A portion of this flow is directed through a cyclone impactor (Brechtel, Inc. Model SCC 0.732) and 0.5 LPM is directed to the CCN. To calculate particle losses, we used a two-step method. First, the measured SMPS size distributions were used to calculate particle loss through the inlet during sampling. Second, the corrected SMPS data was used to calculate the average of the total losses per scan down the CCN line. Then, the correction was applied to the CCN data. This calculation was done separately for each deployment location due to changes in the measured size distributions between locations. Particle loss from diffusion (based on Kesten, 1991 and Gormley, 1949), inertial impaction in 90-degree bends (based on Aerosol Measurement, 2011 and Crane, 1977), and cyclone impactor efficiency (based on Dirgo, 1985) were included in the loss calculation. When the SMPS was not sampling at a location (in the case of an instrument malfunction or operator error), the reported CPC data was corrected with an average of the total losses for the entire campaign at the specified deployment location (e.g., if we needed to correct Galveston data, then the average of all calculated losses at Galveston was taken). These flatline corrections were used for all data on 22/07/13, 22/07/20, 22/07/22, and the data from Galveston on 22/08/09. The supersaturation uncertainty is estimated conservatively at +/- 0.03%, where variation in the inlet temperature, pressure, and calibration technique prevents a more accurate measurement. Confidence in the reported supersaturation measurements is based on a pre-campaign calibration (following the methods from our previous work and Deng, 2014 based on Rose, 2008) in addition to inter-comparisons with the DOE for two days (22/08/18 and 22/09/01) where TAMU was co-located with AMF1. The inter-comparisons show good agreement between our instrument and the DOEs instrument on both days at all supersaturations. After the last inter-comparison on 22/09/01, there was no indication of a malfunction by our instrument through the rest of the campaign. Unfortunately, the instrument was dropped during demobilization. A post-campaign calibration was conducted, which showed a substantial departure from the pre-campaign calibration. The drop may have damaged the instrument’s ability to produce the desired supersaturations. Therefore, we do consider the data after 22/09/01 to be correct, but it should be used with caution. The CCN counter sampled for 3 minutes at each supersaturation setpoint (0.2, 0.4, 0.6, 0.8, 1.0, and 1.2%). At the end of a cycle, the instrument was set to 0.01% supersaturation for 5 minutes. The data is comprised of the last 60 seconds of each supersaturation set point (0.2, 0.4, 0.6, 0.8, 1.0, and 1.2%) to ensure the instrument stabilized and was able to reach thermal equilibrium. We removed the data during the periods where there were operational difficulties, setup, or maintenance. This data was collected for ARM Field Campaign AFC07055 and supported by DOE ASR grant DE-SC0021047. For any further questions, please feel free to contact the instrument PI, Sarah D. Brooks, sbrooks@tamu.edu. Rose et. al. Calibration and Measurement Uncertainties of a Continuous-Flow Cloud Condensation Nuclei Counter (DMT-CCNC): CCN Activation of Ammonium Sulfate and Sodium Chloride Aerosol Particles in Theory and Experiment. Atmos. Chem. Phys., 8, 1153-1179, 2008. Deng et. al. Using Raman Microspectroscopy to Determine Chemical Composition and Mixing State of Airborne Marine Aerosols over the Pacific Ocean. Aerosol Science and Technology, Vol 48, Issue 2, 2014. Kesten et. al. Calibration of a TSI Model 3025 Ultrafine Condensation Particle Counter. Aerosol Science and Technology, 15:2, 107-111, 1991. Gormley et. al. Diffusion from a Stream Flowing through a Cylindrical Tube. Proceedings of the Royal Irish Academy, Vol 52, 163-169, 1948. Aerosol Measurement: Principles, Techniques, and Applications, Third Edition. John Wiley & Sons, Inc, 2011. Crane et. al. Inertial Deposition of Particles in a Bent Pipe. Journal of Aerosol Science, Vol 8, 161-170, 1977. Dirgo et. al. Cyclone Collection Efficiency: Comparison of Experimental Results with Theoretical Predictions. Aerosol Science and Technology, 4:4, 401-415, 1985.

54 ENVIRONMENTAL SCIENCES↗

SMPS data from TAMU TRACER campaign in the Houston TX region from July to September 2022

During TRACER, the Texas A&M Rapid Onsite Atmospheric Measurements Van (ROAM-V) was deployed to capture airmasses behind (maritime) and ahead (continental) of the passage of the sea-breeze front through Houston. On select sampling days, ROAM-V sampled in the morning/mid-day on the coast and then transited to a second inland site for the afternoon/evening. The suite of instruments deployed on ROAM-V included a Condensation Particle Counter (CPC; GRIMM Model 5.403 CPC), Scanning Mobility Particle Sizer (SMPS; TSI 3750 detector, TSI 3082 classifier, TSI 3088 neutralizer, TSI 3081A Differential Mobility Analyzer), Cloud Condensation Nuclei counter (Droplet Measurement Technologies CCN Counter), micro pulse lidar (Droplet Measurement Technologies Micro Pulse LiDAR (miniMPL)), and a Davis Rotating Uniform size-cut Monitor (DRUM; DRUMAir 4-DRUM). Before sampling at each location, the latitude and longitude were recorded using the GPS on the phone application “My Altitude”. Onboard the ROAM-V, aerosol samples are drawn through a shared isokinetic inlet at a flow rate ranging from 3.5 to 7.0 LPM. A portion of this flow, 1.0 LPM, is directed through TSI's 0.071 cm impactor attached to the classifier of the SMPS setup. The SMPS’s DMA and CPC are connected through a 20.3 cm length of 0.48 cm diameter tubing. Measured SMPS size distributions were used to calculate size-dependent particle losses for each SMPS scan. Particle losses from diffusion (based on Kesten, 1991 and Gormley, 1949) and inertial impaction in 90-degree bends (based on Aerosol Measurement, 2011 and Crane, 1977) were included in the loss calculation. This data was collected for ARM Field Campaign AFC07055 and supported by DOE ASR grant DE-SC0021047. For any further questions, please feel free to contact the instrument PI, Sarah D. Brooks, sbrooks@tamu.edu. Kesten et. al. Calibration of a TSI Model 3025 Ultrafine Condensation Particle Counter. Aerosol Science and Technology, 15:2, 107-111, 1991. Gormley et. al. Diffusion from a Stream Flowing through a Cylindrical Tube. Proceedings of the Royal Irish Academy, Vol 52, 163-169, 1948. Aerosol Measurement: Principles, Techniques, and Applications, Third Edition. John Wiley & Sons, Inc, 2011. Crane et. al. Inertial Deposition of Particles in a Bent Pipe. Journal of Aerosol Science, Vol 8, 161-170, 1977.

54 ENVIRONMENTAL SCIENCES↗

Ice nucleation measurements from DRUM impactors during TRACER campaign in the Houston TX region from July to September 2022

During TRACER, three Davis Rotating Uniform size-cut Monitors (DRUM; DRUMAir 4-DRUM) were used to collect aerosols for ice nucleation measurements in the Brooks laboratory at Texas A&M University. The three instruments were located at AMF1 in La Porte, Ancillary site in Guy (ANC), and onboard the Texas A&M Rapid Onsite Atmospheric Measurements Van (ROAM-V). ROAM-V was deployed to capture airmasses behind (maritime) and ahead (continental) of the passage of the sea-breeze front through Houston. On select sampling days, ROAM-V sampled in the morning/mid-day on the coast and then transited to a second inland site for the afternoon/evening. The suite of instruments deployed on ROAM-V included a Condensation Particle Counter (CPC; GRIMM Model 5.403 CPC), Scanning Mobility Particle Sizer (SMPS; TSI 3750 detector, TSI 3082 classifier, TSI 3088 neutralizer, TSI 3081A Differential Mobility Analyzer), Cloud Condensation Nuclei counter (Droplet Measurement Technologies CCN Counter), micro pulse lidar (Droplet Measurement Technologies Micro Pulse LiDAR (miniMPL)), and one of the Davis Rotating Uniform size-cut Monitors (DRUM; DRUMAir 4-DRUM). Before sampling at each location, the latitude and longitude were recorded using the GPS on the phone application “My Altitude”. Each DRUM sampler was operated at a flow rate of 23 LPM. Each DRUM has four stages where the aerodynamic diameter size cuts are as follows: stage 1 larger than 3 μm, stage 2 from 3 to 1.2 μm, stage 3 from 1.2 to 0.34 μm, and stage 4 from 0.34 to 0.15 μm. Pretreated aluminum foil was used as a substrate on all stages. At AMF1 and ANC sites, the DRUMs were operated on the shared aerosol inlet, with generous support of the DOE ARM site staff. These instruments rotated 24 mm per day and only contained aluminum foil substrates. Substrates were changed weekly and transported to Texas A&M for storage in -80C freezer until analysis. The DRUM onboard ROAM-V was operated at a faster rotation rate of 150 mm per day to clearly separate the multiple deployment locations for ROAM-V. For the ROAM-V DRUM, substrates were changed every deployment and transported to Texas A&M for storage in -80C freezer until analysis. At Texas A&M, ice nucleation experiments were conducted to measure the ice nucleation temperature of the ambient aerosol samples collected from the three DRUMs using our previously established procedures (Alsante et al., 2023; Fornea et al., 2009; Matthews et al., 2023). For ice nucleation, only samples collected on stage 3 were analyzed, given that these are the most relevant size (1.2 to 0.34 μm diameter) for potential ice nucleating particles. For the AMF1 and ANC sites, we cut and analyzed 2 mm (2-hour) samples. We analyzed the time periods of the AMF1 site instrument when the ROAM-V was deployed. A 72-hour period from July 11th at 23:49 through July 15th at 1:49 was analyzed from the ANC site instrument. For the ROAM-V instrument, we separated the daily samples by site location. Between 1- and 6-hour independent samples were analyzed at each location. We also cut the ROAM-V samples in half to allow for compositional analysis of the aerosol on the other half of the substrate. All viable samples from the ROAM-V were analyzed. Analysis was done using a custom-built ice nucleation apparatus, recently updated to include an array of 16 individual samples (Matthews et al., 2023). On our experimental setup, we used 100 μL of Ultra-High-Performance Liquid Chromatography (UHPLC) water (Sigma Aldrich, >99.9% purity) to wash off the aerosol from the DRUM substrate. Then, we micropipetted 2 μL droplet samples into each of the 16 wells of the array, using hydrophobically coated microscope slides. Experiments would cycle 28 times from 10 C to -40C over a 20-hour period. During analysis of the TRACER samples, nine experiments were conducted with UHPLC water process blanks that followed an identical preparation procedure. The average freezing temperature and standard deviation for these process blanks is -27.7±2.4 C. This data was collected for ARM Field Campaign AFC07023 and supported by DOE ASR grant DE-SC0021047. For any further questions, please feel free to contact the instrument PI, Sarah D. Brooks, sbrooks@tamu.edu. Alsante, A. N., Thornton, D. C., & Brooks, S. D. (2023). Ice nucleation catalyzed by the photosynthesis enzyme RuBisCO and other abundant biomolecules. Communications Earth & Environment, 4(1), 51. Fornea, A. P., Brooks, S. D., Dooley, J. B., & Saha, A. (2009). Heterogeneous freezing of ice on atmospheric aerosols containing ash, soot, and soil. Journal of Geophysical Research: Atmospheres, 114(D13). DOI:10.1029/2009JD011958 Matthews, B. H., Alsante, A. N., & Brooks, S. D. (2023). Pollen Emissions of Subpollen Particles and Ice Nucleating Particles. ACS Earth and Space Chemistry.

54 ENVIRONMENTAL SCIENCES↗

Mini-Micropulse Lidar data from TAMU TRACER campaign in the Houston TX region from July to September 2022

During TRACER, the Texas A&M Rapid Onsite Atmospheric Measurements Van (ROAM-V) was deployed to capture airmasses behind (maritime) and ahead (continental) of the passage of the sea-breeze front through Houston. On select sampling days, ROAM-V sampled in the morning/mid-day on the coast and then transited to a second inland site for the afternoon/evening. The suite of instruments deployed on ROAM-V included a Condensation Particle Counter (CPC; GRIMM Model 5.403 CPC), Scanning Mobility Particle Sizer (SMPS; TSI 3750 detector, TSI 3082 classifier, TSI 3088 neutralizer, TSI 3081A Differential Mobility Analyzer), Cloud Condensation Nuclei counter (Droplet Measurement Technologies CCN Counter), micro pulse lidar (Droplet Measurement Technologies Micro Pulse LiDAR (mini-MPL)), and a Davis Rotating Uniform size-cut Monitor (DRUM; DRUMAir 4-DRUM). Before sampling at each location, the latitude and longitude were recorded using the GPS on the phone application “My Altitude”. The mini-MPL deployed with ROAM-V is a 532 nm elastic and polarization lidar. The mini-MPL outputs normalized relative backscatter (NRB) derived from raw signal after after-pulse, overlap, and dead-time correction calibration. The depolarization ratio is calculated from the co-polarized and cross-polarized NRB (Flynna et al., 2007). The NRB and depolarization ratio data are resampled from the original data at 1-minute intervals. The vertical resolution of the mini-MPL data is 15 meters. The mini-MPL data can be used to determine the boundary layer, cloud top, and cloud bottom height and can be used to retrieve aerosol type and concentration profile. This data was collected for ARM Field Campaign AFC07055 and supported by DOE ASR grant DE-SC0021047. For any further questions, please feel free to contact the instrument PI, Sarah D. Brooks, sbrooks@tamu.edu . Flynna, C. J., Mendozaa, A., Zhengb, Y., & Mathurb, S. (2007). Novel polarization-sensitive micropulse lidar measurement technique. Optics express, 15(6), 2785-2790.

54 ENVIRONMENTAL SCIENCES↗

Inter-ELM pedestal evolution and the role of edge fluctuations in the C-Mod and DIII-D tokamaks

Edge localized modes (ELMs) lead to a cyclical behaviour of the H-mode pedestal density, temperature and pressure. Substantial evidence exists associating the ELM crash with violation of ideal MHD stability, via current driven kink/peeling modes and/or pressure gradient driven ballooning modes. Recovery from ELM crashes and buildup to the next ELM crash is an active and critical area of edge physics research for ITER projections. In one set of theories, the pedestal pressure profile in H-mode discharges is predicted to be limited by micro-instabilities. One such micro-instability is the kinetic ballooning mode (KBM), which is hypothesized to provide a ‘soft’ limit that regulates the edge transport, thereby restricting the local pressure gradient. In this picture, e.g. in the EPED model, the pedestal width expands slowly until the ideal MHD stability limit is reached. Experiments were recently performed on the C-Mod and DIII-D devices to search for instabilities correlated with the pedestal evolution between ELMs. The results show correlations between the onset of quasi-coherent fluctuations between type I ELMs and a critical temperature gradient. Linear gyrokinetic calculations have shown that these fluctuations have characteristics similar to those expected for KBMs. These results provide additional data toward validation of the EPED model, increasing confidence in ITER projections.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Properties of soil pore space regulate pathways of plant residue decomposition and community structure of associated bacteria

The goal of this study is to explore interactions between plant detritus and the micro-scale characteristics of physical micro-environments, that is, soil pores, and their influence on decomposition, on CO2 emission, and on composition of bacterial communities associated with the detritus. The study consisted of a series of soil incubation experiments with samples of contrasting pore characteristics with/without plant residue, accompanied by analyses of soil pores and phylogenetic analysis of microbial communities with rRNA genes via pyrosequencing.

16S rDNA↗

Ion conductive inks and solutions for additive manufacturing of lithium microbatteries

A separator made of ion conductive ink is produced by additive manufacturing. A micro-battery is produced with the separator made of ion conductive ink located between the battery's anode and cathode. The separator functions to keep the anode and cathode apart and to facilitate the transport of ions to produce an operative micro-battery.

25 ENERGY STORAGE↗

Thermoset composite having thermoplastic characteristics

A composite composition includes a thermoset resin and about 3 wt. % to about 35 wt. % of at least one material selected from the group consisting of cellulose nanofibrils (CNF), micro-sized cellulose fibers (MFC), and cellulose nanocrystals (CNC) dispersed therein as measured with respect to the overall weight of the composite composition. The cellulose nanofibrils and/or nanocrystals have an average diameter of about 5 nm to about 500 nm and an average aspect ratio in the range of about 5:1 to about 500:1. The cellulose micro-sized fibers have an average diameter of about 5 μm to about 100 μm and an average aspect ratio in the range of about 5:1 to about 250:1.

Ozcan, Soydan↗

Mechanical Characterization of Fe-Co-2V (Hiperco): Fatigue/Monotonic Testing Hardness Testing and Fractography

Fe-Co-2V is a popular metallic alloy used in electromagnetic applications. However, there is a lack of mechanical fatigue characterization of this alloy in the literature. In this work, Fe-Co-2V specimens with rectangular cross-sections were carefully prepared in accordance with standards. They were measured for surface roughness and then subjected to quasi-static monotonic testing, as well as fatigue testing at both 0.5 Hz and 1 Hz frequencies. Both Rockwell hardness and Vickers micro- hardness testing were performed. Additionally, scanning electron microscopy imaging of the fractured surfaces was done. The quasi-static testing revealed a flat yield region characteristic of Laders bands. Here, the fatigue results did not show significant differences or sensitivity to change in frequency, although the fatigue life was higher on average for the 0.5 Hz. However, the fatigue results differed from published work at 0.33 Hz. The fractography revealed purely brittle fracture, with clear chevron marks and fracture initiation always starting at the surface. Lastly, it was identified that the C, D, and F Rockwell hardness scales were appropriate for testing this material and that the grain size necessitated the use of the upper end of indentation force for Vickers micro-hardness testing.

36 MATERIALS SCIENCE↗

Phase Stability of Yttrium Titanium Oxide

This proposed study aims at elevating Idaho National Laboratory (INL)’s portfolio in nuclear material research on two major fronts: 1) expanding INL’s material characterization capabilities to provide holistic microstructural and microchemical characterization ranging from atomic scale to millimeter scale, and 2) filling the knowledge gap on the effect of microstructural evolution on material phase stability at extreme conditions resembling those inside nuclear reactors, using Yttrium-Titanium-Oxide (YTO) as a model material. Previous research indicated the kinetics of phase transition of YTO materials varies between bulk samples and powder samples, suggesting that microstructural characteristics such as defect, micro-strain, and crystallite size could play a significant role in phase transition. The effect of crystallite size on the thermodynamics of phase transition has been well documented for other ceramic materials at nanometer crystallite size, with potential impacts from surface and strain energy and defects. In this proposed study, we will perform microstructural (micro-strain, crystallite size, defects, phase) and microchemical (elemental mapping) analyses through in-situ high temperature measurements using X-ray diffraction (XRD; at millimeter scale for powder and bulk samples) and transmission electron microscopy (TEM, at nanometer scale and atomic scale for powder and thin foil samples), to provide a comprehensive view of the effect of microstructural and microchemical evolution on phase transition and phase stability of YTO materials. These findings will also establish a roadmap and provide new insights on the phase stability of other materials that are critical to nuclear energy and other renewable energy infrastructure. Besides advancing our understanding of this fundamental material science question, this project will also enable the development of state-of-the-art material characterization capabilities at INL/MFC for microstructural and microchemical analysis at high temperature conditions. The new collaboration between the High-Resolution Materials Characterization group at INL and the Electron Microscopy group at the University of Florida (UF) in this project will open the possibilities for more fruitful and synergetic cutting-edge nuclear material research in the future.

36 MATERIALS SCIENCE↗

Emulsion stereolithography and 3D printing of multimaterials and nanoscale material gradients

A functionally graded material is formed by pipetting individual micro-or-nano-litter droplets with a variety of materials including multi-nanostructured material (nanowires, carbon nanotubes, enzymes, multi-element and/or multi-color, multi-biomolecules) and UV polymerization of the flat hydrogel meniscus surface formed at the carrier fluid interface. After step-by-step droplet pipetting and subsequent layer-by-layer UV polymerization via a digital mask, the complete fabricated part without supporting layers is taken out of the carrier fluid while the un-cured micro-litter residue is conveniently suctioned out of the carrier fluid.

Zheng, Xiaoyu↗

Micromobility Integrated Transit and Infrastructure for Efficiency (MITIE)

Nearly omnipresent in many cities of all sizes across the United States, micromobility vehicles-e-scooters, manual bicycles, e-bicycles, and larger seated electric scooters-are notably missing from SMART Mobility research. This project aims to expand the spectrum of modes currently being researched within SMART Mobility by exploring micromobility as an important tool toward meeting energy-efficient mobility goals. It expands on findings from SMART Mobility 1.0 that revealed preferences to reduce transportation-related expenses through use of a network of mobility-as-a-service (MaaS) and other shared mobility options, and builds on findings from a 2019 Vehicle Technology Analysis Program (VTAP) funded micromobility project conducted by our team. We will explore multiple facets of micromobility, including behavior and decision-making, the integration of micromobility within transportation infrastructure, energy estimates, and operations. Guiding research questions include: (1) What are the potential energy savings from low, medium, and high market penetration of micromobility (in passenger, multimodal, and freight domains)? (2) Which scenarios for micromobility use and related enablement of increased public transit use should be modeled/considered in the SMART 2.0 Workflow? (3) To what degree can micromobility supplement/complement transit system operations? (4) What are people's preferences towards micromobility? How do preferences vary across various sociodemographic segments? How can this knowledge inform operations? (5) What are optimal strategies to attain high user adoption and shift users toward more energy-efficient mode choices in terms of micromobility operation? How do these strategies affect energy savings, person-miles traveled, lifecycle energy use, and adoption rates? These questions will be addressed through applied research in five project emphasis areas: (1) Energy estimates of micromobility for Workflow scenarios: Expand and refine previous micromobility work to augment the Workflow approaches to modeling urban travel. (2) Multimodal connection with transit: Utilizing Mobility-Energy Productivity (MEP) tools to evaluate multimodal travel patterns enabled by micromobility, including assessing how to reduce barriers of inequity of access to mobility options and destinations. (3) Mode choice, induced demand, and infrastructure: Understanding the mode shift induced through micromobility to inform energy impact analysis. (4) Energy optimization of micromobility operations: Identification of micromobility operations parameters and development of operations scenarios to better understand present-day micromobility operations for integration into the Workflow, in partnership with BEAM and POLARIS modeling teams. (5) Micro-freight: Characterize the current state of micro-freight activities, including energy effects and geospatial analyses, to inform Workflow.

ADVANCED PROPULSION SYSTEMS,POWER TRANSMISSION AND↗

Corrosion evaluation of metal foams in eutectic molten salts for high temperature latent heat energy storage application

High-temperature Thermal Energy Storage (TES) has drawn great attention as a technology that can increase the role and profitability of micro nuclear reactors in the decentralized clean energy market. Various research needs have been proposed by Idaho National Laboratory (INL) in "the Integrated Energy Systems: 2020 Roadmap" with the goal of utilizing the high temperature of 550 degrees or more generated in the 4th generation reactor to industrial purposes from the standpoint of integrated energy systems [1]. With the recent development of the 4th generation nuclear power plant, including micro nuclear reactor, there is a great deal of interest in researching how to efficiently couple a heat source to an industrial process through thermal processing. Texas A&M University (TAMU) and INL are currently collaborating to develop a novel latent heat storage design called HITB (Heat pipe-Integrated Thermal Battery). As part of the small-scale experimental demonstration research for HITB, a study for storage medium selection was conducted at TAMU. Eutectic salts have attracted interest as high-temperature heat storage medium for HITB. Especially, chloride molten salts and fluoride molten salts are considered promising candidates due to their high melting temperature, thermal stability, and high latent heat of fusion. Since eutectic salts have poor thermal conductivity in general, it is critical to distribute materials with high thermal conductivity evenly to facilitate the charging and discharging of heat. In this study, metal foam was considered in the HITB system to overcome the poor heat transfer characteristics of eutectic salts. In order to improve heat transfer, it is necessary to study materials with high thermal conductivity, corrosion resistant to molten salts, such as fins, extended surfaces, particles, microcapsulation, or foam structure. Porous structure of copper or aluminum can increase heat transfer area, form a thermal transfer network, and increase the effective thermal conductivity of thermal storage medium [2]. Since the melting temperature is required to be at least 450? in the current HITB design, various eutectic salts are being considered. FLiNaK and FLiBe, which are famous for fluoride salts, are good candidates, but due to the sharp rise in the price of LiF recently, they are excluded for economic reasons to be applied to large-capacity thermal energy storage. On the other hand, chloride salts are very cheap and easy to obtain, have a high melting temperature, and have a high latent heat of fusion, so they are recently in the spotlight as a phase change material. However, because of the hygroscopic nature of chloride salts, HCl gas due to impurity is easy to be released and is particularly vulnerable to corrosion. Chloride eutectic salts have been tested and suggested for metal alloys that are particularly resistant to corrosion, such as SS304, SS316, Hastelloy, Inconel 625, Incoloy 800H, which has low thermal conductivity, and is very expensive [3-6]. Porous materials with high thermal conductivity such as copper and aluminum have been tested for stability in fluids such as paraffin or water as metal foam or metal fin structures, but high temperature corrosion tests were not performed on various eutectic salts yet. Therefore, this study investigated the high temperature corrosion characteristics of metal alloys, such as C10100 foam, C10100 plate, 6101 alloy foam, and SS316 plate, while immersed in the candidate eutectic salts. A total of 20 tests for SS316 coupons and 10 tests for C10100 coupons were performed to ensure the repeatability of the present measurements. Since it is difficult to completely remove the salt inside metal foam due to the complex inner structure of the metal foam, only the surface condition was observed with a microscopy and scanning electron microscopy (SEM) image, except for measuring the corrosion rate and average mass loss.

25 ENERGY STORAGE↗

Micromobility Integrated Transit and Infrastructure for Efficiency (MITIE)

Nearly omnipresent in many cities of all sizes across the United States, micromobility vehicles-e-scooters, manual bicycles, e-bicycles, and larger seated electric scooters-are notably missing from SMART Mobility research. This project aims to expand the spectrum of modes currently being researched within SMART Mobility by exploring micromobility as an important tool toward meeting energy-efficient mobility goals. It expands on findings from SMART Mobility 1.0 that revealed preferences to reduce transportation-related expenses through use of a network of mobility-as-a-service (MaaS) and other shared mobility options, and builds on findings from a 2019 Vehicle Technology Analysis Program (VTAP) funded micromobility project conducted by our team. We will explore multiple facets of micromobility, including behavior and decision-making, the integration of micromobility within transportation infrastructure, energy estimates, and operations. Guiding research questions include: 1) what are the potential energy savings from low, medium, and high market penetration of micromobility (in passenger, multimodal, and freight domains)? 2) which scenarios for micromobility use and related enablement of increased public transit use should be modeled/considered in the SMART 2.0 Workflow? 3) to what degree can micromobility supplement/complement transit system operations? 4) what are people's preferences towards micromobility? How do preferences vary across various sociodemographic segments? How can this knowledge inform operations? 5) what are optimal strategies to attain high user adoption and shift users toward more energy-efficient mode choices in terms of micromobility operation? How do these strategies affect energy savings, person-miles traveled, lifecycle energy use, and adoption rates? These questions will be addressed through applied research in five project emphasis areas: 1) energy estimates of micromobility for Workflow scenarios: Expand and refine previous micromobility work to augment the Workflow approaches to modeling urban travel; 2) multimodal connection with transit: Utilizing Mobility-Energy Productivity (MEP) tools to evaluate multimodal travel patterns enabled by micromobility, including assessing how to reduce barriers of inequity of access to mobility options and destinations; 3) mode choice, induced demand, and infrastructure: Understanding the mode shift induced through micromobility to inform energy impact analysis; 4) energy optimization of micromobility operations: Identification of micromobility operations parameters and development of operations scenarios to better understand present-day micromobility operations for integration into the Workflow, in partnership with BEAM and POLARIS modeling teams; 5) micro-freight: Characterize the current state of micro-freight activities, including energy effects and geospatial analyses, to inform Workflow.

ADVANCED PROPULSION SYSTEMS↗

Process and apparatus for continuous production of porous structures

An apparatus and process are presented for continuous production of metal-based micro-porous structures of pore sizes from 0.3 nm to 5.0 μm from a green part of characteristic diffusion mass transfer dimension less than 1 mm through chemical reactions in a continuous flow of gas substantially free of oxygen. The produced micro-porous structures include i) thin porous metal sheets of thickness less than 200 μm and pore sizes in the range of 0.1 to 5.0 μm, ii) porous ceramic coating of thickness less than 40 μm and ceramic particle sizes of 200 nm or less on a porous metal-based support structures of pore sizes in the range of 0.1 to 5 μm.

Liu, Wei↗

Method for micromolding a polymeric membrane having a pore array

A method for micro-molding a polymeric membrane and including pouring a predetermined volume of curable polymer unto a micro-fabricated mold having a post array with pillars, and overlaying the polymer with a support substrate. A spacer, such as a rubber spacer, is placed in contact with the support substrate and a force is applied to an exposed side of the spacer to compress the support substrate and the polymer together. While applying the force, the polymer is cured on the mold for a predetermined time period and at a predetermined temperature to form a polymeric membrane having a pore array with a plurality of pores corresponding to the plurality of pillars of the post array. The polymeric membrane is removed from the support substrate.

36 MATERIALS SCIENCE↗

Image-Based Digital Twin for Assessing the Coupled Electro-Chemo-Mechanical Behavior of Li-Ion Batteries

In energy storage materials, strong electrochemical-mechanical coupling and highly anisotropic material properties contribute to the formation and propagation of micro-cracking during charge/discharge cycling, resulting in reduced performance and service life. In this work, a digital twin is created to investigate the performance of a Li-ion battery cathode and simulate degradation accumulation. Pixel-based model construction is used to represent the complex material geometries from microstructural images supplied by the National Renewable Energy Laboratory (NREL). Because of the expected large deformation and crack opening, the reproducing kernel particle method (RKPM), a meshfree method with discretization at the image pixels, is used to approximate the field variables: electrostatic potential, concentration, and displacement. An interface modified reproducing kernel (IM-RK) is constructed by scaling a smooth kernel function with an interface-distance function to achieve strategic discontinuity types (i.e. weak discontinuities for strain discontinuities and strong discontinuities for cracks) and alleviate Gibbs oscillations near these transition zones. The discrete nature of the images' pixel points is employed throughout the model and approximation construction. The mechanical model is verified using an image-based microstructure under tensile loading. A transient electro-chemo-mechanical coupled simulation is performed to evaluate the potential micro-cracking induced degradation of the battery cathode material subjected to charge/discharge cycling.

battery degradation↗