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Filtered by Artificial Intelligence, Ecosystem Science, Explosives Detection, Hydrogen & Fuel Cells, Integrative Omics, Science of Interfaces, Secure & Adaptive Systems, Terrestrial Aquatics, Vehicle Energy Storage, and Wind Energy
SEPTEMBER 17, 2020
Web Feature

Not Your Average Refinery

In a new review, PNNL researchers outline how to convert stranded biomass to sustainable fuel using electrochemical reduction reactions in mini-refineries powered by renewable energy.
SEPTEMBER 14, 2020
Web Feature

VOLTTRON™ Goes to School

The PNNL-developed VOLTTRON™ software platform’s advancement has benefited from a community-driven approach. The technology has been used in buildings nationwide, including most recently on a university campus.
Web Feature

When Nano Meets Bio

Pacific Northwest National Laboratory (PNNL) is part of a continuing National Science Foundation (NSF) team investigating the environmental impact of nanoparticles at the molecular level.

Secretary of Energy Advisory Board (SEAB) Report Recognizes PNNL Contributions

ML and AI

Report features how PNNL’s computing capabilities are affecting the nation’s security, science, and energy missions

August 25, 2020
August 25, 2020

Contributions from researchers across Pacific Northwest National Laboratory (PNNL) were recognized in the preliminary findings of a Secretary of Energy Advisory Board (SEAB) report from a working group dedicated to the U.S. Department of Energy’s (DOE’s) capabilities and future in artificial intelligence (AI) and machine learning. PNNL researchers’ expertise is prominent throughout DOE’s AI efforts, particularly in the areas of data sciences and national security.

Based largely on input from DOE sponsors, the report features how PNNL’s computing capabilities are affecting the nation’s security, science, and energy missions. Key highlights include:

  • Studying how AI affects the global landscape for securing nuclear materials, potentially using deep learning to enhance physical and digital protections against material concealment, delivery, theft, and sabotage.
  • Describing how the United States and its partners might employ deep learning to combat attack efforts for enhanced nuclear security.
  • Designing advanced deep learning models to characterize operations with buildings, using electrical signatures on power lines, enabling new designs for energy-efficient buildings in addition to enhanced security features for nuclear facilities.
  • Leading the nuclear explosive monitoring project with data scientists working to significantly lower detection thresholds of low-yield, evasive underground nuclear explosions without increasing time-to-detection or the amount of human analysis.
  • Co-design of advanced accelerator, memory and data movement concepts to support convergence of AI and machine learning methods with other forms of data analytics and traditional scientific high performance computing (HPC). 

The report highlights PNNL’s support to the National Nuclear Security Administration, featuring joint laboratory collaborations between PNNL and others, including the Y-12 National Security Complex, Sandia National Laboratories, Lawrence Livermore National Laboratory, Los Alamos National Laboratory, and Oak Ridge National Laboratory. Additionally, PNNL is working as part of DOE’s comparative advantages in AI, providing the Office of Energy Efficiency and Renewable Energy access to AI subject matter experts.

View full preliminary findings of the Secretary of Energy Advisory Board (SEAB) report.

For more information about PNNL’s research contributions, contact Aaron Luttman

Study Shows Coastal Wetlands Aid in Carbon Sequestration

data collection in marsh

PNNL scientist, Amy Borde collects data in a marsh on the Columbia River estuary.

Photo: Heida Diefenderfer

Sea-level rise impacts will likely decrease ecosystem carbon stocks

August 13, 2020
August 13, 2020

Tidal marshes, seagrass beds, and tidal forests are exceptional at absorbing and storing carbon. They are referred to as total ecosystem carbon stocks, yet little data exists quantifying how much carbon is absorbed and stored by tidal wetlands in the Pacific Northwest (PNW). Knowing this information is valuable, particularly in the context of sea level rise and with the associated need for Earth system modeling to predict changes at the coast.

The Science

Researchers found that the average total ecosystem carbon stock in the PNW is higher than in other areas of the U.S. and other parts of the world. Marsh carbon stocks, in particular, are twice the global average. Researchers found progressive increases in total ecosystem carbon stocks along the elevation gradient of coastal wetland types common in the PNW: seagrass, low marshes, high marshes, and tidal forests. Total carbon also increased along the salinity gradient, with more carbon occurring in lower salinity areas.

Additionally, this research showed that common methods used to estimate soil carbon actually underestimate soil carbon stocks in coastal wetlands. Soil carbon storage below the depth of 100 centimeters proved to be an important carbon pool in PNW tidal wetlands.

The Impact

The results suggest that long-term sea-level rise impacts, such as tidal inundation and increased soil salinity, will likely decrease ecosystem carbon stocks. This is a concern if wetlands can’t migrate with increased sea level due to being bound by topography and human development.  


This research arose from the Pacific Northwest Blue Carbon Working Group, of which Amy Borde and Heida Diefenderfer of Pacific Northwest National Laboratory’s Coastal Sciences Division are members. The team studied 28 tidal ecosystems across the PNW coast, from Humboldt Bay, California, to Padilla Bay, Washington. They sampled common coastal wetland types that occur along broad gradients of elevation, salinity, and tidal influences, collecting the data necessary to calculate total carbon stocks in both above ground biomass and the soil profile.

In three years of study, the researchers found that most carbon is in the wetland soils not aboveground, and much of it is deeper than one meter—a typical lower limit of sampling. Total ecosystem carbon stocks progressively increased along the terrestrial-aquatic gradient of coastal wetland ecosystems common in the temperate zone including seagrass, low marshes, high marshes, and tidal forests. The findings were reported in “Total Ecosystem Carbon Stocks at the Marine-Terrestrial Interface: Blue Carbon of the Pacific Northwest Coast, USA,” published in the August 2020 online edition of Global Change Biology (DOI: 10.1111/gcb.15248).

Research Team: PNNL’s Amy Borde and Heida Diefenderfer, along with J. Boone Kauffman, Leila Giovanonni, James Kelly, Nicholas Dunstan, and Christopher Janousek (Oregon State University); Craig Cornu and Laura Brophy (Institute for Applied Ecology/Estuary Technical Group); and Jude Apple (Padilla Bay National Estuarine Research Reserve).


The grant award was administered by the Institute of Applied Ecology, and other partners included Oregon State University and the Padilla Bay National Estuarine Research Reserve. This research was supported by the National Oceanic and Atmospheric Administration, through a cooperative agreement with the University of Michigan. 


Kauffman, J Boone, Leila Giovanonni, James Kelly, Nicholas Dunstan, Amy Borde, Heida Diefenderfer, Craig Cornu, Christopher Janousek, Jude Apple, and Laura Brophy. “Total Ecosystem Carbon Stocks at the Marine‐terrestrial Interface: Blue Carbon of the Pacific Northwest Coast, United States.” Global change biology, no. 0 (August 11, 2020). DOI: 10.1111/GCB.15248

August 11, 2020

Deconstructing the Soil Microbiome

shovel in soil with tiny green plants around

Microbes in the soil play a major role in nutrient cycling and plant health, but the inherent complexity of the soil microbiome makes it challenging to effectively analyze microbial functions and relationships. 

Image courtesy of Lukas from Pexels

Deconstruction of soil microbial communities into discrete functional groups enables piecing together the functional potential of the complex soil microbiome

July 23, 2020
July 23, 2020

The Science                                

The soil microbiome plays a major role in nutrient cycling and plant health. However, its inherent complexity, with a vast array of microbes that metabolize many different molecules, makes it challenging to effectively analyze ecosystem functions performed by interacting members of soil microbial communities. Researchers dissected the complex microbial community of a native Washington soil into reproducible, low-complexity communities called 'functional modules.' Because these subcommunities are easier to study than a bulk community, researchers could analyze microbial species and functions present in the soil in more depth than before.

The Impact

By studying discrete functional components of the soil microbiome at high resolution, the researchers obtained a more complete picture of soil diversity compared to analysis of the entire soil community. They identified specific evolutionary relationships and biochemical characteristics of the soil microbiome that otherwise would have been hidden in previous community-scale genomic analyses. Improved understanding of the functions of the soil microbiome could help scientists harness beneficial aspects of the soil microbiome to increase soil health or crop productivity.  


One gram of soil contains microbes from thousands of different evolutionary groups. These microbes also have a wide variety of metabolic functions that help them survive in different soil microenvironments. Analyzing the complete functional and taxonomic diversity of a soil microbiome requires a large amount of computing power, and it may fail to capture large populations of quiet or rare microbes.

To simplify the analysis of a soil microbial community, researchers incubated a parent soil microbiome under several different conditions to create different subcommunities of microbes with specific functions, or functional modules. The functional modules included: usage of simple and complex carbon substrates, antibiotic resistance, anaerobic growth with different redox acceptors, and stress resistance. For each functional module, the researchers performed 16S rRNA gene amplicon sequencing to determine the community composition and RNA sequencing to identify expressed functions. Approximately 27% of unique taxa present in the parent soil were found in the functional modules, in addition to 341 taxa not detected in the parent community. The functional modules had unique gene expression patterns that were also enriched for transcripts associated with functional characteristic of each module. By dissecting the soil microbiome into discrete components, the researchers obtained a more comprehensive and highly detailed view of a soil microbiome and its biochemical potential than through analysis of a soil microbiome as a whole.


Ryan McClure, Pacific Northwest National Laboratory,


This research was supported by the U.S. Department of Energy’s Office of Science, Biological and Environmental Research Program and is a contribution of the Scientific Focus Area “Phenotypic response of the soil microbiome to environmental perturbations.”

D. Naylor, et al., “Deconstructing the Soil Microbiome into Reduced-Complexity Functional Modules.” mBio 11, e01349-20 (2020). [DOI: 10.1128/mBio.01349-20]

JULY 9, 2020
Web Feature

Building a Better Battery—Faster

Researchers at PNNL have developed a software tool that helps universities, small business, and corporate developers to design better batteries with new materials that hold more energy.

Digging into the Details of Phosphorus Availability

Photo of plant with roots under ground

Courtesy of Shutterstock

New root blotting technique visualizes relationship between root growth, microbial activity, and soil nutrients.

July 7, 2020
July 7, 2020

The Science

Phosphorous is an important nutrient for plants. However, the mechanisms used by plants to extract phosphorus from soil and incorporate it into their biomass are not well understood. Now, researchers developed a new technique to visualize the activity and distribution of enzymes that mobilize phosphate around plant roots. Tracking the location of these enzymes can help researchers better understand the chemical dynamics between roots, microbes, and soil that influence how plants get nutrients. The approach could also be applied to other nutrient-cycling enzymes.

Diagram showing rhizosphere blotting nondestructive process
A new root blotting technique produces an imprint of plant roots growing in flat slabs. The paper imprints can then be probed with different fluorescent indicators to visualize both the distribution and activity of phosphate-mobilizing enzymes surrounding the roots.

The Impact

Phosphorus is an essential nutrient for plants and therefore, global demand for phosphorus fertilizers is expected to grow to accommodate the world’s growing population. However, most of these fertilizers are made from rock phosphorus, a non-renewable resource. This research provides new insights into the complex dynamics of phosphorous exchange between soil, microbes, and plant roots. Knowledge from this newly developed approach will help scientists identify strategies to improve phosphorus use efficiency for bioenergy crop production in marginal environments, as well as for agriculture in general.


Soil bacteria, fungi, and plants produce enzymes called phosphatases, which convert organic sources of phosphorus into a form that plants can absorb. Researchers have studied the microbial activity in bulk soil samples, providing information about the overall functional potential of the environment. But to better understand the dynamics between soil, plants, and microbes, more detail is needed. To accomplish that, a team of researchers developed a new technique based on root blotting to reveal phosphatase activity and distribution around plant roots. They grew switchgrass in flat pots or “rhizoboxes” containing soil with pellets of root matter as sources of organic phosphorus. Then, they applied a nitrocellulose membrane to capture proteins around the roots. Finally, the researchers stained the membrane with fluorescent indicators for phosphatase activity and protein concentration. This revealed the spatial distribution of phosphatase around the roots of plants, and highlighted regions of increased phosphatase activity.

This approach could be used to study phosphatase activity over time, as well as other nutrient-cycling enzymes. The combination of membrane extraction, with rapid analysis via fluorescent probes to reveal localization of phosphatase activity in the rhizosphere, offers a new technique for environmental applications. Expanding this approach could enable simultaneous visualization of multiple enzyme types in soil systems.


Development of this method was funded by DOE’s Office of Science, Biological and Environmental Research Program by the Early Career Research Award program (PI: Jim Moran).


V.S. Lin, et al. “Non-destructive spatial analysis of phosphatase activity and total protein distribution in the rhizosphere using a root blotting method.” Soil Biology and Biochemistry, 146 (2020). DOI: 10.1016/j.soilbio.2020.107820

Predicting Soil CO2 Emissions from Air Temperature

graph with multicolored dots

The mean annual air temperature and precipitation coverage of soil respiration samples used in this study, by ecosystem type. The gray dotes represent worldwide data points.

A cheaper, more efficient way to estimate soil respiration and carbon flux

June 2, 2020
June 2, 2020

The Science

Soil respiration—the flow of CO2 from the soil surface to the atmosphere—is one of the largest carbon fluxes in the terrestrial biosphere. In recent DOE-funded study, researchers created a model that predicted annual soil respiration in different parts of the world based on average air temperature for each region.

The Impact

Monitoring greenhouse gas exchange between the soil and the atmosphere is important in tracking worldwide CO2 emissions. Despite this, many regions are either inaccessible or do not have the resources to undertake rigorous research to monitor soil respiration. In this study, researchers found that soil respiration measured at annual mean temperature can be used to predict annual soil respiration. The findings could be used to reduce soil respiration measurement frequency and greatly decrease cost-- enabling easier measurements in low income and inaccessible regions worldwide.


Led by Jinshi Jian of Pacific Northwest National Laboratory, this internationally diverse research collaboration used data from more than 800 site-year observations worldwide. The team developed a predictive model to test the relationship between annual soil respiration and instant soil respiration rate at mean annual temperature among diverse ecosystems and climates throughout the world. Air temperature data is more common than soil temperature data, making it a more achievable measurement to gauge carbon emissions in lower income countries. Their results were recently published in Agricultural and Forest Meteorology.

PNNL Contact

Jinshi Jian, Pacific Northwest National Laboratory,


This research was supported by the DOE Office of Biological and Environmental Research (BER), as part of BER’s Terrestrial Ecosystem Science Program [number: DE-AC05-76RL01830].


Jian, J., Bahn, M., Wang, C., Bailey, V. L., Bond-Lamberty, B. Prediction of annual soil respiration from its flux at mean annual temperature. Agricultural and Forest Meteorology. Volume 287. DOI: 10.1016/j.agrformet.2020.107961