Engineering topics
Yang, Fan
Publications and source records attributed to Yang, Fan.
The microbiome structure of decomposing plant leaves in soil depends on plant species, soil pore sizes, and soil moisture content
Microbial communities are known as the primary decomposers of all the carbon accumulated in the soil. However, how important soil structure and its conventional or organic management, moisture content, and how different plant species impact this process are less understood. To answer these questions, we generated a soil microcosm with decomposing corn and soy leaves, as well as soil adjacent to the leaves, and compared it to control samples. We then used high-throughput amplicon sequencing of the ITS and 16S rDNA regions to characterize these microbiomes. Leaf microbiomes were the least diverse and the most even in terms of OTU richness and abundance compared to near soil and far soil, especially in their bacterial component. Microbial composition was significantly and primarily affected by niche (leaves vs. soil) but also by soil management type and plant species in the fungal microbiome, while moisture content and pore sizes were more important drivers for the bacterial communities. The pore size effect was significantly dependent on moisture content, but only in the organic management type. Overall, our results refine our understanding of the decomposition of carbon residues in the soil and the factors that influence it, which are key for environmental sustainability and for evaluating changes in ecosystem functions.
Modeling Future Demand for EV Charging Infrastructure [Slides]
U.S. climate goals for economy-wide net-zero greenhouse gas emissions by 2050 require rapid decarbonization of the light-duty vehicle fleet and plug-in electric vehicles (EVs) are poised to become the preferred technology for achieving this end. Considerable investments in public and private EV charging infrastructure will be needed to support widespread adoption, however, guidance is lacking on when, where, and what types of chargers will be needed. In this PLMA Load Management Dialogue session, researchers from the National Renewable Energy Laboratory (NREL) discuss findings from a recent quantitative assessment of the charging network requirements to support high penetrations of light-duty EVs by 2030. The study produced multiple detailed network growth trajectories at the national, state, and local levels that serve as a guidepost for future planning. In addition, an overview of NREL's publicly accessible EV infrastructure tools and data sets, designed to support planning and decision-making for EV infrastructure stakeholders, is provided.
Evaluation of Four Ground-based Retrievals of Cloud Droplet Number Concentration in Marine Stratocumulus with Aircraft In Situ Measurements
Cloud droplet number concentration (N d ) is crucial for understanding aerosol-cloud interactions (ACI) and associated radiative effects. We present evaluations of four ground-based N d retrievals based on comprehensive datasets from the Atmospheric Radiation Measurements (ARM) Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) field campaign. The N d retrieval methods use ARM ENA observatory ground-based remote sensing observations from a Micropulse lidar, Raman lidar, cloud radar, and the ARM NDROP Value-added Product (VAP), all of which also retrieve cloud effective radius (r e ). The retrievals are compared against aircraft measurements from the Fast-Cloud Droplet Probe (FCDP) and the Cloud and Aerosol Spectrometer (CAS) obtained from low-level marine boundary layer clouds on 12 flight days during summer and winter seasons. Additionally, the in situ measurements are used to validate the assumptions and characterizations used in the retrieval algorithms. Statistical comparisons of the probability distribution function (PDF) of the N d and cloud r e retrievals with aircraft measurements demonstrate that these retrievals align well with in situ measurements for overcast clouds, but they may substantially differ for broken clouds or clouds with low liquid water path (LWP). The retrievals are applied to four years of ground-based remote sensing measurements of overcast marine boundary layer clouds at the ARM ENA observatory to find that N d (r e ) values exhibit seasonal variations, with higher (lower) values during the summer season and lower (higher) values during the winter season. The ensemble of various retrievals using different measurements and retrieval algorithms such as those in this paper can help to quantify N d retrieval uncertainties and identify reliable N d retrieval scenarios. Of the retrieval methods, we recommend using the using the Micropulse lidar-based method given its good agreement with in situ measurements, it has less sensitivity to issues arising from precipitation and low cloud LWP/optical depth, and it has broad applicability by functioning for both day and nighttime conditions.
Modeling U.S. Light-Duty Demand for EV Charging Infrastructure in 2030
With the support of DOE's Vehicle Technologies Office and the DOE/DOT Joint Office (JO), NREL has applied the EVI-X modeling suite to conduct a National Electric Vehicle Infrastructure Needs Assessment. This report considers a 2030 scenario in which 50% of light-duty sales are electric (including plug-in hybrids), resulting in an on-road stock of 33 million vehicles. We consider the needs of vehicles used for typical daily driving, drivers without access to residential charging, corridor charging supporting long-distance travel, and ride-hailing electrification. We find that a cumulative capital investment of $82 billion in public and private charging infrastructure will be necessary in our baseline scenario (approximately 3x greater than our estimate of planned investments to date). This result is framed as a conservative estimate as the assumed costs include charging equipment and installation but exclude the cost of grid upgrades and distributed energy resources.
The 2030 National Charging Network: Estimating U.S. Light-Duty Demand for Electric Vehicle Charging Infrastructure
With the support of DOE's Vehicle Technologies Office and the DOE/DOT Joint Office (JO), NREL has applied the EVI-X modeling suite to conduct a National Electric Vehicle Infrastructure Needs Assessment. This report considers a 2030 scenario in which 50% of light-duty sales are electric (including plug-in hybrids), resulting in an on-road stock of 33 million vehicles. We consider the needs of vehicles used for typical daily driving, drivers without access to residential charging, corridor charging supporting long-distance travel, and ride-hailing electrification. We find that a cumulative capital investment of $82 billion in public and private charging infrastructure will be necessary in our baseline scenario (approximately 3x greater than our estimate of planned investments to date). This result is framed as a conservative estimate as the assumed costs include charging equipment and installation but exclude the cost of grid upgrades and distributed energy resources.
Metabolic and transcriptomic study of pennycress natural variation identifies targets for oil improvement
Pennycress (Thlaspi arvense L.), a member of the Brassicaceae family, produces seed oil high in erucic acid, suitable for biodiesel and aviation fuel. Although pennycress, a winter annual, could be grown as a dedicated bioenergy crop, an increase in its seed oil content is required to improve its economic competitiveness. The success of crop improvement relies upon finding the right combination of biomarkers and targets, and the best genetic engineering and/or breeding strategies. In this work, we combined biomass composition with metabolomic and transcriptomic studies of developing embryos from 22 pennycress natural variants to identify targets for oil improvement. The selected accession collection presented diverse levels of fatty acids at maturity ranging from 29% to 41%. Pearson correlation analyses, weighted gene co‐expression network analysis and biomarker identifications were used as complementary approaches to detect associations between metabolite level or gene expression and oil content at maturity. The results indicated that improving seed oil content can lead to a concomitant increase in the proportion of erucic acid without affecting the weight of embryos. Processes, such as carbon partitioning towards the chloroplast, lipid metabolism, photosynthesis, and a tight control of nitrogen availability, were found to be key for oil improvement in pennycress. Besides identifying specific targets, our results also provide guidance regarding the best timing for their modification, early or middle maturation. Thus, this work lays out promising strategies, specific for pennycress, to accelerate the successful development of lines with increased seed oil content for biofuel applications.
Scattering of phonons by edge dislocation and thermal conductivity of nanocrystalline silicon
For this work, the temperature dependent thermal conductivity of nanocrystalline silicon with the grain size of 500 nm, 144 nm, and 76 nm, was calculated based on the intrinsic phonon properties using a first-principles-based method and recent analytical theory of phonon-dislocation scattering. The results demonstrate, in the nanocrystalline silicon, that the low temperature (T) limit of thermal conductivity is directly proportional to T 2 instead of the conventional Casimir limit of T 3 . Calculated frequency-dependent scattering rates also indicate regimes of dominant scattering mechanisms: frequency-independent boundary scattering dominates in the very low phonon frequency regime of less than 0.6 THz; frequency-dependent boundary scattering dominates in the intermediate phonon frequency regime between 0.6 and 6 THz; and Umklapp scattering dominates in the high phonon frequency regime beyond 6 THz. The thermal conductivity is linear proportional to nanograin size in the region of d < 100nm and it shows independence at d > 1μm. This work proves the importance of dislocation-phonon scattering to thermal conductivity when the size of nanograins is small or at low temperature.
Observational Investigation of the Effect of Turbulence on Microphysics and Precipitation in Warm Marine Boundary Layer Clouds
Abstract Turbulence is omnipresent in the marine boundary layer (MBL) and several mechanisms have been proposed regarding its role on MBL cloud microphysics. In particular, past modeling studies suggested that increasing turbulence broaden the droplet size distribution (DSD) and leads to precipitation initiation, this suggested relationship has not been evaluated yet using long‐term observations. Here, comprehensive retrievals from long‐term ground‐based observations are used to explore the impact of turbulence on microphysics and precipitation in drizzling MBL clouds. Our analysis supports that broader DSD and larger droplets are observed with strong turbulence, but interestingly, the precipitation is reduced instead of being enhanced. This suppression mechanism is mainly due to the entrainment and mixing process in which the entrained dry air evaporates cloud water. This study provides observational evidence to show the complex effect of turbulence on MBL cloud properties and implies the potential influence of turbulence on the clouds lifetime.
A high-capacity Sn metal anode for aqueous acidic batteries
Aqueous acidic batteries as a good choice to respond battery diversity, delivering safety, cost, environmental friendliness and high-power necessary for renewable energy storage. However, the practical adoption is greatly challenged by low-voltage and energy density due to the inadequate metal anode materials. Here we report an interfacial regulated Sn metal anode as the solution of the last piece of the puzzle. In this study, the ease of recycling, low potential, fast redox kinetics, and high capacity of Sn perfectly fit the battery system, and the Sn metal shedding critical issue is successfully suppressed by promoting uniform deposition for added interaction from alloying. Consequently, this reversible Sn anode with 442 mAh g -1 matches well to different types of cathodes. The as-assembled acidic batteries also demonstrate sufficient output voltage (up to 1.7 V), energy density (up to 312 Wh kg -1 based on both electrodes), kinetics (up to 24 C) and stability (up to 2400 cycles).
An Intercomparison of Large‐Eddy Simulations of a Convection Cloud Chamber Using Haze‐Capable Bin and Lagrangian Cloud Microphysics Schemes
Abstract Recent in situ observations show that haze particles exist in a convection cloud chamber. The microphysics schemes previously used for large‐eddy simulations of the cloud chamber could not fully resolve haze particles and the associated processes, including their activation and deactivation. Specifically, cloud droplet activation was modeled based on Twomey‐type parameterizations, wherein cloud droplets were formed when a critical supersaturation for the available cloud condensation nuclei (CCN) was exceeded and haze particles were not explicitly resolved. Here, we develop and adapt haze‐capable bin and Lagrangian microphysics schemes to properly resolve the activation and deactivation processes. Results are compared with the Twomey‐type CCN‐based bin microphysics scheme in which haze particles are not fully resolved. We find that results from the haze‐capable bin microphysics scheme agree well with those from the Lagrangian microphysics scheme. However, both schemes significantly differ from those from a CCN‐based bin microphysics scheme unless CCN recycling is considered. Haze particles from the recycling of deactivated cloud droplets can strongly enhance cloud droplet number concentration due to a positive feedback in haze‐cloud interactions in the cloud chamber. Haze particle size distributions are more realistic when considering solute and curvature effects that enable representing the complete physics of the activation process. Our study suggests that haze particles and their interactions with cloud droplets may have a strong impact on cloud properties when supersaturation fluctuations are comparable to mean supersaturation, as is the case in the cloud chamber and likely is the case in the atmosphere, especially in polluted conditions.
Seasonal activities of the phyllosphere microbiome of perennial crops
Understanding the interactions between plants and microorganisms can inform microbiome management to enhance crop productivity and resilience to stress. Here, we apply a genome-centric approach to identify ecologically important leaf microbiome members on replicated plots of field-grown switchgrass and miscanthus, and to quantify their activities over two growing seasons for switchgrass. We use metagenome and metatranscriptome sequencing and curate 40 medium- and high-quality metagenome-assembled-genomes (MAGs). We find that classes represented by these MAGs (Actinomycetia, Alpha- and Gamma- Proteobacteria, and Bacteroidota) are active in the late season, and upregulate transcripts for short-chain dehydrogenase, molybdopterin oxidoreductase, and polyketide cyclase. Stress-associated pathways are expressed for most MAGs, suggesting engagement with the host environment. We also detect seasonally activated biosynthetic pathways for terpenes and various non-ribosomal peptide pathways that are poorly annotated. Our findings support that leaf-associated bacterial populations are seasonally dynamic and responsive to host cues.
ShadeLab/PAPER_Howe_2023_switchgrass_MetaT
The raw data (metagenomes and metatranscriptomes) for this study are available in the Joint Genomes Institute Genome Portal (https://genome.jgi.doe.gov/portal/ Project ID 503249) with projects designated by year and product type. The MAG genomes analyzed in this paper are available on NCBI, as bioproject PRJNA800073. Plants and microorganisms form beneficial associations. Understanding plant-microbe interactions will inform microbiome management to enhance crop productivity and resilience to stress. Here, we apply a genome-centric approach to identify ecologically important leaf microbiome members on field-grown switchgrass and miscanthus and to quantify their activities for switchgrass over two growing seasons. We integrate metagenome and metatranscriptome sequencing from 192 leaf samples collected over representative time points in crop phenology. We curated 40 medium- and high-quality metagenome-assembled-genomes (MAGs) and focused analysis on seasonal transcript recruitment to them. Classes represented by these focal MAGs (Actinomycetia, Alpha- and Gamma- Proteobacteria, and Bacteroidota) were active and had increases in transcripts for short-chain dehydrogenase, molybdopterin oxidoreductase, and polyketide cyclase in the late season. The majority of MAGs had activated stress-associated pathways, including trehalose metabolism, indole acetic acid degradation, betaine biosynthesis, and reactive oxygen species degradation, suggesting direct engagement with the host environment. We also detected seasonally activated biosynthetic pathways for terpenes (carotenoids and isoprenoids) and for various non-ribosomal peptide pathways that were poorly annotated. Overall, this study overcame laboratory and bioinformatic challenges associated with field-based leaf metatranscriptome analysis to inform both general and likely specialized activities of these phyllosphere populations. These activities collectively support that leaf-associated bacterial populations are seasonally dynamic, responsive to host cues, and interactively engage in feedback with the plant. This analysis represented quality filtering of metagenomes and metatranscriptomes (data-preparation folder), metagenome assemblies (metagenome-assembly folder) and metagenome-assembled genome binning, curation, refinement, annotation (mag-evaluation folder). Abundances of sequencing libraries were calculated based on reads mapped (mapping folder). Additionallly, analysis of our annotated results are also included (analysis folder).
Scaling of Turbulence and Microphysics in a Convection–Cloud Chamber of Varying Height
Abstract The convection–cloud chamber enables measurement of aerosol and cloud microphysics, as well as their interactions, within a turbulent environment under steady‐state conditions. Increasing the size of a convection–cloud chamber, while holding the imposed temperature difference constant, leads to increased Rayleigh, Reynolds and Nusselt numbers. Large–eddy simulation coupled with a bin microphysics model allows the influence of increased velocity, time, and spatial scales on cloud microphysical properties to be explored. Simulations of a convection–cloud chamber, with fixed aspect ratio and increasing heights of H = 1, 2, 4, and (for dry conditions only) 8 m are performed. The key findings are: Velocity fluctuations scale as H 1/3 , consistent with the Deardorff expression for convective velocity, and implying that the turbulence correlation time scales as H 2/3 . Temperature and other scalar fluctuations scale as H −3/7 . Droplet size distributions from chambers of different sizes can be matched by adjusting the total aerosol injection rate as the horizontal cross‐sectional area (i.e., as H 2 for constant aspect ratio). Injection of aerosols at a point versus distributed throughout the volume makes no difference for polluted conditions, but can lead to cloud droplet size distribution broadening in clean conditions. Cloud droplet growth by collision and coalescence leads to a broader right tail of the distribution compared to condensation growth alone, and this tail increases in magnitude and extent monotonically as the increase of chamber height. These results also have implications for scaling within turbulent, cloudy mixed‐layers in the atmosphere, such as fog layers.
Silver nanoparticle enhanced metal-organic matrix with interface-engineering for efficient photocatalytic hydrogen evolution
Integrating plasmonic nanoparticles into the photoactive metal-organic matrix is highly desirable due to the plasmonic near field enhancement, complementary light absorption, and accelerated separation of photogenerated charge carriers at the junction interface. The construction of a well-defined, intimate interface is vital for efficient charge carrier separation, however, it remains a challenge in synthesis. Here we synthesize a junction bearing intimate interface, composed of plasmonic Ag nanoparticles and matrix with silver node via a facile one-step approach. The plasmonic effect of Ag nanoparticles on the matrix is visualized through electron energy loss mapping. Moreover, charge carrier transfer from the plasmonic nanoparticles to the matrix is verified through ultrafast transient absorption spectroscopy and in-situ photoelectron spectroscopy. The system delivers highly efficient visible-light photocatalytic H 2 generation, surpassing most reported metal-organic framework-based photocatalytic systems. This work sheds light on effective electronic and energy bridging between plasmonic nanoparticles and organic semiconductors.
Reversible Iron Oxyfluoride (FeOF)–Graphene Composites as Sustainable Cathodes for High Energy Density Lithium Batteries
Two large barriers are impeding the wide implementation of electric vehicles, namely driving-range and cost, primarily due to the low specific energy and high cost of mono-valence cathodes used in lithium-ion batteries. Iron is the ideal element for cathode materials considering its abundance, low cost and toxicity. However, the poor reversibility of (de)lithiation and low electronic conductivity prevent iron-based high specific energy multi-valence conversion cathodes from practical applications. In this work, a sustainable FeOF nanocomposite is developed with extraordinary performance. The specific capacity and energy reach 621 mAh g –1 and 1124 Wh kg –1 with more than 100 cycles, which triples the specific capacity, and doubles the specific energy of current mono-valence intercalation LiCoO 2 . This is the result of an effective approach, combing the nanostructured FeOF with graphene, realized by making the (de)lithiation reversible by immobilizing FeOF nanoparticles and the discharge products over the graphene surface and providing the interparticle electric conduction. Importantly, it demonstrates that introducing small amount of graphene can create new materials with desired properties, opening a new avenue for altering the (de)lithiation process. Finally, such extraordinary performance represents a significant breakthrough in developing sustainable conversion materials, eventually overcoming the driving range and cost barriers.
High-Efficiency Reversible Alkaline Membrane Fuel Cells
The proposed project will explore oxidation-resistant alkaline membrane/ionomers and corrosion-resistant bifunctional catalysts to enable reversible alkaline membrane fuel cells (AMFCs). The project will for the first time demonstrate a reversible AMFC with greater than 50% RTE at 1000 mA/cm 2 without introducing any salts or bases in the aqueous feed.
Chemical vapour deposition of Fe-N-C oxygen reduction catalysts with full utilization of dense Fe-N4 sites
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