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Oxide interfaces in disarray

Microscope image, bright blue background with bright green oxides

Atomic-scale imaging informs interface models for oxygen defect formation during disordering of oxides used in energy and computing.

| PNNL

Exploration of disorder at material interfaces could lead to better device performance

March 3, 2020
March 3, 2020
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The structure of an interface at which two materials meet helps determine the performance of the computers and other devices we use every day. However, understanding and controlling interface disorder at the atomic level is a difficult materials science challenge.

A research team at PNNL and Texas A&M University combined cutting edge imaging and numerical simulations to examine disordering processes in widely used oxide materials. They found that certain oxide interface configurations remain stable in extreme environments, suggesting ways to build better performing, more reliable devices for fuel cells, space-based electronics, and nuclear energy.

Visualizing the disordering process

As reported in Advanced Materials Interfaces (Asymmetric Lattice Disorder Induced at Oxide Interfaces,” DOI: 10.1002/admi.201901944) the team set out to examine interfaces between pyrochlore-like and perovskite oxides, two common classes of functional materials used in energy and computing technologies. While most past work has focused on individual bulk materials, less attention has been paid to interfaces connecting them, as would be the case in a device. In particular, it is not clear how interface features, such as composition, bonding, and possible defects, govern disordering processes.

Funded by PNNL’s Nuclear Process Science Initiative (NPSI), the team employed experimental and theoretical methods to study the interface at different stages of disorder introduced through ion irradiation. They imaged the local structure of the material using high-resolution scanning transmission electron microscopy and convergent beam electron diffraction, which showed that the bulk of the two materials disordered (amorphized) before the interface. After further irradiating the material, they found that a band region near the interface had remained crystalline, while the rest of the structure had become amorphous.

To understand this behavior, the team turned to a technique called electron energy loss spectroscopy, which allowed them to examine the atomic-scale chemistry and defects formed at the interface. Their measurements revealed the presence of substantial amounts of defects called oxygen vacancies, which can greatly affect properties such as magnetism and conductivity. Based on these observations, the team constructed a theoretical model of the interface and explored the effect of different interface configurations on the tendency to form vacancies.

“In our model we are able to systematically vary interface features, such as crystal structure, intermixing, and strain, to see their effect on defect formation. We found that the structure of the materials on both sides of the interface can influence where defects are likely to form first,” explained Steven R. Spurgeon, a PNNL materials scientist. “Our model suggests that by selecting appropriate crystal structures and controlling how they connect, it may be possible to dictate the sequence of defect formation, which would allow us to enhance the properties of these materials.”

The team is exploring other interface structures and chemistries, with an eye toward improving the performance of oxides used in extreme environments.

The study was conducted as part of the NPSI project, “Damage Mechanisms and Defect Formation in Irradiated Model Systems,” led by Spurgeon.

Research Team

Steven Spurgeon (PNNL), Tiffany Kaspar (PNNL), Vaithiyalingam Shutthanandan (Environmental Molecular Sciences Laboratory at PNNL), Jonathan Gigax (Texas A&M), Lin Shao (Texas A&M), Michel Sassi (PNNL).
February 20, 2020
JANUARY 10, 2020
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Clark Recognized for Nuclear Chemistry Research

The world’s largest scientific society honored Sue B. Clark, a PNNL and WSU chemist, for contributions toward resolving our legacy of radioactive waste, advancing nuclear safeguards, and developing landmark nuclear research capabilities.
DECEMBER 6, 2019
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Converging on Coastal Science

Advancing a more collective understanding of coastal systems dynamics and evolution is a formidable scientific challenge. PNNL is meeting the challenge head on to inform decisions for the future.
NOVEMBER 26, 2019
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Conquering Peak Power

PNNL’s Intelligent Load Control technology manages and adjusts electricity use in buildings when there’s peak demand on the power grid.
NOVEMBER 13, 2019
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Let There Be (Acceptable) Light

Advancements such as LEDs have changed consumers’ experience with lighting. Whereas there was once a simple choice of how much light a consumer desired, there’s now a variety of choices to be made about the appearance of light.

Moments Matter When It Comes to Modeling Rain

Rain

Getting rain properties correct in atmospheric models is critical for accurately representing the structure and evolution of cloud systems.

Improved representation of rain microphysics led to more accurate simulations of surface precipitation

March 12, 2019
October 22, 2019
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The Science
In atmospheric models, raindrop properties such as rainfall rate are usually described based on the raindrop size distribution. For example, heavy rain rates may have a wider raindrop size distribution than light rain. To improve predictions of rain that reaches the surface, the primary question has been, how can models better represent the evolution of raindrop size distribution in space and time in the atmosphere? A team led by researchers at the U.S. Department of Energy’s (DOE) Pacific Northwest National Laboratory improved the representation of rain microphysics by predicting the shape parameter of raindrop size distributions in a recently developed cloud microphysics scheme. They found that under a wide range of atmospheric conditions, their advanced representation delivered surface rain properties similar to those produced by a benchmark scheme, but with less computational resources.

The Impact
Because raindrops play a major role in the vertical redistribution of heat and moisture in the atmosphere, they are a critical component for modeling the structure and evolution of cloud systems such as mesoscale convective systems. These systems are major sources of heavy rain in the central United States. A proper representation of rain in numerical models is not only vital to predict surface precipitation, but also to accurately simulate environmental conditions and circulation patterns. The advanced rain microphysics representation from this study improves simulations of rain properties under various atmospheric conditions, and it can be used to increase accuracy of weather and climate models. The scheme will be implemented in DOE’s Energy Exascale Earth System Model (E3SM).

Summary
Cloud microphysics schemes in weather and climate models usually predict two moments—the total number and mass—of the raindrop size distribution. Researchers upgraded the Predicted Particle Properties (P3) cloud scheme by adding another predicted variable—shape parameter—for raindrop size distribution, turning the two-moment scheme into a three-moment scheme for raindrop representation. They also developed and incorporated a new parameterization for drop-drop collisions—when two drops collide—and the breakup of large drops into smaller ones. 
To evaluate those new developments, the research team tested them with an idealized rain model. The model simulated 450 rain scenarios that were initialized by different raindrop size distributions and environmental conditions. Researchers compared the simulated surface rain properties against those from a detailed and computationally costly reference scheme. The team found that, depending on initial rain intensity, up to 95 percent of simulations with the new developments produced raindrop sizes and surface rain rates within ±20 percent biases from the reference results. This was a considerable improvement from the original two-moment scheme, which only reached 4 percent using the same criteria for comparisons with the reference results. Sensitivity tests showed that both the added degree of freedom—the additional variable for raindrop size distribution—and the new process parameterization contributed to the improvements.

PI Contact
Jiwen Fan, Pacific Northwest National Laboratory, jiwen.fan@pnnl.gov  

Funding
This research was supported by the Climate Model Development and Validation program funded by the Office of Biological and Environmental Research in the U.S. Department of Energy Office of Science. Model simulations were performed using PNNL Institutional Computing.

Paukert M, J Fan, PJ Rasch, H Morrison, JA Milbrandt, J Shpund, and A. Khain. 2019. “Three-Moment Representation of Rain in a Bulk Microphysics Model.” Journal of Advances in Modeling Earth Systems 11(1):257−277, https://doi.org/10.1029/2018MS001512.

Influence of Groundwater Extraction Costs and Resource Depletion Limits on Simulated Global Nonrenewable Water Withdrawals over the 21st Century

Groundwater

Recent PNNL research suggests that rising groundwater extraction costs will force users to turn to other sources of water.

Global groundwater depletion is projected to peak and then decline during this century as costs of using it change

April 16, 2019
October 22, 2019
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The Science
Because water is a fundamental human need, estimating future supplies is important. Researchers at the U.S. Department of Energy’s Pacific Northwest National Laboratory (PNNL) coupled regionally varying groundwater availability and extraction cost estimates with continually adjusted demands for water in a simulation that covered multiple sectors around the world. As groundwater levels dropped, imposing greater capital and energy costs to bring water to the surface, modeled water use sectors responded by drawing from other water resources. These behaviors resulted in a marked peak and decline in the rate of global groundwater depletion.

The Impact
Previously it was assumed that the rate of global groundwater depletion would increase steadily over the 21st century as humans demanded more water—particularly for crop production. This work suggests that groundwater depletion may actually decline, because the increasing costs of pumping will force water users to adapt by turning to less expensive sources, which are often in regions where renewable water remains plentiful.

Summary
In many regions of the world, groundwater reserves are being depleted rapidly. This raises concerns for the sustainability of irrigated agriculture and global food supplies. It is therefore important to study groundwater depletion and possible exhaustion of water resources at a global scale. A problem for such analysis is the lack of detailed understanding of when a depleting resource becomes unviable for further exploitation. The question is not simply how much water is physically available; we need to know when the financial costs and environmental effects of extracting more groundwater render the resource unviable for human applications. To study these effects, PNNL researchers employed a global, gridded data set that specifies the cost of groundwater extraction as a function of depletion. Then, using the Global Change Assessment Model (GCAM), they simulated water users as economic decision makers to understand how they would adapt as extraction costs increased. Results indicated that future rates of global groundwater depletion would be heavily moderated by increasing extraction costs. Regions that depleted water to costly levels lost competitive advantage for crop production, which shifted to regions where water resources were less costly and more plentiful. The team concluded that extraction costs must be included in simulations for projections of global groundwater depletion to be reliable.

PI Contact
Leon Clarke, Pacific Northwest National Laboratory, leon.clarke@pnnl.gov

PNNL Contact
Mohamad Hejazi, Pacific Northwest National Laboratory, Mohamad.Hejazi@pnnl.gov  

Funding
This research was supported by the U.S. Department of Energy Office of Science, Biological and Environmental Research through the Multisector Dynamics, Earth and Environmental System Modeling Program. 

Turner SWD, M Hejazi, C Yonkofski, SH Kim, and P Kyle. 2019. “Influence of Groundwater Extraction Costs and Resource Depletion Limits on Simulated Global Nonrenewable Water Withdrawals Over the Twenty-First Century.” Earth’s Future 7(2):123−135. https://doi.org/10.1029/2018ef001105.

Calibrating Building Energy Demand Models to Refine Long-Term Energy Planning

Bend

The BEND model can combine information on building technologies, climate, and population to forecast hourly building energy demand for regions the size of electric power balancing authorities. This calibration aligns the results with historical data to make them more accurate.

A new, flexible calibration approach improved model accuracy in capturing year-to-year changes in building energy demand

June 6, 2019
October 22, 2019
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The Science
Aggregated building energy demand models, which are based on combining the outcomes of many individual building simulations, are an emerging tool for long-term energy planning at multiple spatial scales. They can be used to understand and project changes in building energy demand due to changes in population, climate, and building technologies. However, these models can be hard to calibrate because real-world data availability at the appropriate temporal, spatial, and sectoral scales is often limited. A new approach developed at the U.S. Department of Energy’s (DOE’s) Pacific Northwest National Laboratory (PNNL) allows these aggregate models to be calibrated at multiple scales. Researchers used this new method to calibrate PNNL’s Building ENergy Demand (BEND) aggregate model. Once calibrated, BEND successfully captured year-to-year changes in building energy demand due to changes in weather.

The Impact
Unlike more traditional statistical methods, physically based aggregate models such as BEND can fully capture the dynamic relationships between hourly building energy demand and population, climate, and building technologies. As a result, these models are valuable tools for understanding multisectoral dynamics. The new approach allows BEND and other aggregate models to be calibrated at the scale at which they will be applied, overcoming a key limitation of this class of models. Models such as BEND will improve model projections of future building energy demand at different scales and refine long-term energy planning through integration with grid operations and resource planning models.

Summary
PNNL’s BEND model is one of an emerging class of models designed to capture total and hourly building energy demand resulting from the aggregation of tens to hundreds of thousands of individual building simulations. Historically, these aggregate models have proven difficult to calibrate because there is a limited amount of target data available at relevant space, time, and sectoral scales. Researchers developed and demonstrated a novel approach to calibrate BEND, using approximately 100,000 individual simulations of DOE’s EnergyPlus model, against the best available data at the geographic scale of balancing authorities (electricity management subregions). Once calibrated, BEND captured year-to-year changes in total and peak building energy demand due to variations in weather within these areas. The study applied PNNL’s new calibration approach to the western United States, but the method can be applied to regions across the world with similar data and scale challenges. Researchers also suggested areas in which improved data collection and sharing would help to further refine these emerging models.

PI Contact
Jennie Rice, Pacific Northwest National Laboratory, jennie.rice@pnnl.gov
Ian Kraucunas, Pacific Northwest National Laboratory, ian.kraucunas@pnnl.gov 

Funding
This research was supported by the DOE Office of Science as part of research in the MultiSector Dynamics, Earth and Environmental System Modeling Program. A portion of the research was performed using PNNL’s Institutional Computing resources. 

Taylor ZT, Y Xie, CD Burleyson, N Voisin, and I Kraucunas. 2019. “A multi-scale calibration approach for process-oriented aggregated building energy demand models.” Energy and Buildings 191:82‒94. https://doi.org/10.1016/j.enbuild.2019.02.018.

A Global Hydrologic Framework to Accelerate Scientific Discovery

Hydro

A new version of the Xanthos global hydrology model enables researchers to rapidly address complex multisector dynamics science challenges, such as determining water scarcity impacts on land use, and could help accelerate energy-water-land research even more.

A new version of the Xanthos model enables researchers to rapidly address evolving energy-water-land science challenges

June 11, 2019
October 22, 2019
Highlight

The Science
Research in energy-water-land systems—and understanding how water scarcity can affect these systems—is rapidly progressing. To quantify changes in—and the effects of—future freshwater availability, a team from the U.S. Department of Energy’s Pacific Northwest National Laboratory (PNNL) developed the Xanthos global hydrology model, which can be used independently or as a part of a coupled modeling system. Researchers can use Xanthos to explore how different climate, socioeconomic, or energy scenarios affect regional and global water availability over the 21st century. In version 2 of the model, the PNNL team built a component-based framework to rapidly incorporate and test new hydrologic process modules—or code—within a robust environment, complete with diagnostics and calibration capabilities.

The Impact
Within Xanthos version 2, scientists can easily incorporate and test evolving hydrologic process models as components, or selectable, compatible parts of the Xanthos framework. For example, researchers can customize a specific configuration of components to address the role of snowmelt in characterizing drought or to explore the role of model assumptions in characterizing the uncertainty of complex coupled energy-water-land systems. The process of incorporating and testing models within the component-based framework is faster than what it would take to reproduce an entire configuration of models if users added their own from scratch. The usability of Xanthos version 2 enables researchers to rapidly address complex multisector dynamics science challenges, such as determining water scarcity impacts on land use, and could help accelerate energy-water-land research even more.

Summary
Xanthos, an open-source model written in Python, provides a solid foundation for continued advances in global water dynamics science. The model simulates historical and future global water availability on a monthly time step at a spatial resolution of 0.5 geographic degrees. Xanthos also can serve as the freshwater supply component of the Global Change Assessment Model (GCAM), also developed at PNNL. 
For Xanthos version 2, the PNNL team built upon the original version by creating a component-based framework in which users can swap out or extend previously existing core components of the model—potential evapotranspiration (PET), runoff generation, and river routing—without starting from scratch. For example, users can now swap out the potential evapotranspiration core component with one they think captures the dynamics of the systems and processes they are trying to model. The component-style architecture of Xanthos version 2 enables researchers to quickly incorporate and test the latest energy-water-land research in a stable modeling environment with prebuilt diagnostics. The PNNL team also created a robust default configuration that includes a calibration module, hydropower modules, and new PET modules. These enhancements are now available to the scientific community in Xanthos version 2, which can be downloaded from GitHub.

PI Contact
Mohamad Hejazi, Pacific Northwest National Laboratory, Mohamad.Hejazi@pnnl.gov

Funding
This research was supported by the U.S. Department of Energy Office of Science as part of research in the MultiSector Dynamics, Earth and Environmental System Modeling program.

Vernon CR, MI Hejazi, SWD Turner, Y Liu, CJ Braun, X Li, and RP Link. 2019. “A Global Hydrologic Framework to Accelerate Scientific Discovery.” Journal of Open Research Software 7(1):1, http://doi.org/10.5334/jors.245.