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DOE OSTI2020

Developing Metrics to Evaluate the Skill and Credibility of Downscaling

In this project, our overarching goal was to evaluate the skill and credibility of statistical and dynamical downscaling techniques for reconstructing the historical climate record and projecting future climate change. This report summarizes our approach and accomplishments. In the first year of the project, the priority was to generate new data sets. For Year 2, the overall goal was to focus comparisons during the historical period and for a subset of variables, especially temperature and precipitation. In Year 3 and beyond, the focus was mainly on comparisons and metrics for future climate change simulations. To quantify the uncertainty associated with gridded dataset choice, the UCLA group compared eight gridded temperature datasets, examining climatologies, variability, and trends. The Scripps group completed statistical downscaling of NARR with the LOCA method, and UCLA and Scripps collaborated on a comparison of historical and end-of-century temperature and precipitation patterns over California from WRF, LOCA-WRF, and LOCA-Livneh. In addition to downscaling temperature and precipitation, the Scripps group has spent considerable time working on near-surface wind and humidity downscaling. The Santa Clara group assembled the Variable Infiltration Capacity (VIC) for nine snow-dominated river basins draining the western slopes of the Sierra Nevada range and assessed the role of snow albedo feedback in their VIC simulations. The results will help inform future downscaling studies.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Updating Hadron Production Models to Better Predict Neutrino Flux for DUNE

The Deep Underground Neutrino Experiment (DUNE) is an ongoing project at Fermilab with international collaboration and over 190 institutions involved. DUNE has three primary science goals, one of which is searching for the origin of the imbalance of matter and antimatter in the universe. Accomplishing this goal will require the study of neutrinos and the phenomenon of neutrino oscillation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

ChIMES: A Machine-Learned Interatomic Model Targeting Improved Description of Condensed Phase Chemistry in Energetic Materials

In this report we detail completion of a Physics and Engineering Model Level Two Milestone targeting improved reactive interatomic potentials (IAPs) for energetic materials (EM) through machine learning. The specific goals of this milestone were to develop, validate, and document a new reactive molecular dynamics method for EM, based on machine learning by (1) generating databases of first-principles-derived forces, stresses, and energies for HN3 and 3,4-bis(3-nitrofurazan- 4-yl)furoxan (DNTF) (2) generate atomistic force fields from these databases via ML, and (3) benchmark model performance against first principles calculations. These goals were achieved by (1) further developing a machine learned reactive IAP and generation approach (i.e. the Chebyshev Interaction Model for Efficient Simulation or “ChIMES”), for which resulting IAPs can approach the predictive power of quantum-mechanical approaches at a fraction of the computational expense, and (2) applying the ChIMES framework to develop models for HN3 and DNTF. We find that for simple energetic materials like HN3, high accuracy ChIMES models can be obtained through application of a fitting approach that does not use active machine learning. We demonstrate the suitability of ChIMES models for simulations involving EM by using the HN3 model in multiscale shock technique simulations to predict the HN3 Chapman-Jouguet detonation state and investigate chemical evolution out to 1 ns following shock compression. This model is then used in larger direct shock (DS) simulations for a preliminary investigation of how bubbles (i.e. voids) influence material response under shock compression. We find that more complex EM (i.e. DNTF) necessitate a more sophisticated fitting approach, and develop a new active learning method and python tool to meet this challenge. We demonstrate that this fitting approach yields ChIMES models that out-perform commonly used standard reactive IAPs as well as semi-empirical quantum methods, and discuss the systematic improvability of these actively learned ChIMES models. We also describe challenges related to model development for EM such as DNTF, for which few experimental or previous simulation data are available (e.g. which could otherwise inform generation of training data). To overcome this issue, we establish a semi-empirical quantum ChIMES capability which can be used to efficiently map out relevant thermodynamic and configurational space, and generate ChIMES-IAP training data in a multiscale manner. We also show that these semi-empirical quantum ChIMES models can be used to generate predictions for the shock Hugoniot (the Hugoniot is the locus of thermodynamic states found in a shocked material) equation of state, investigate related thermochemistry, and explore carbon condensation following shock compression. This work represents a substantial advance in our atomistic modeling capability for EM that will provide much needed information on the chemistry of detonation for continued development of continuum models based on the Cheetah thermochemical code.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Multiphysics Proxy Modeling for CCS [Slides]

In a presentation for the GEM Lab Research Group Meeting, the motivation, goals, methods, and results of the study were described. The study's overall goal is to develop an initial proxy model for the leakage of CO 2 from a deep saline aquifer through a fault.

58 GEOSCIENCES↗

DOE OSTI2020

Ready for Renewables: Grid Planning and Competitive Renewable Energy Zones (CREZ) in the Philippines

The Department of Energy of the Philippines launched the competitive renewable energy zones (CREZ) process to help achieve the country's goals of scaling up renewable energy generation on the power system and to ensure sustainable, secure, reliable, accessible, and affordable energy. The CREZ process identifies the most economic renewable energy resource areas so transmission planning and expansion can accelerate their development. By proactively focusing transmission expansion to these resource areas, renewable energy generation development obstacles such as transmission access, energy curtailment, land permitting (such as protected or high-slope areas), and regulatory barriers are easier to overcome thus, reducing risk for private sector renewable energy investment. This report is will cover the outputs of the CREZ process, the development of the outputs through stakeholder-driven coordination, and how this process will help the Philippines achieve their renewable energy goals.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Community Solar for the Southeast (Final Report)

The Community Solar for the Southeast project provided technical assistance for cooperative and municipal utilities in the southeastern United States that are considering community solar programs. The project provided generally applicable information for these utilities in the form of an implementation guide and other freely available materials. It also provided detailed technical assistance to specific utilities in the form of feasibility analyses for possible community-scale solar (and energy storage) projects and program designs for community solar programs, all at no direct cost to the utilities. By helping to spur development of community solar projects in a region that historically had not seen much community-scale solar development, the program provided proof-of-concept for other community solar projects in the region, and helped to open up a market segment (cooperative and municipal utilities) that may have otherwise lacked the resources to independently pursue community solar development. The overall goal of the project was an expansion of community solar capacity at municipal and cooperative utilities in the southeastern United States (in this case meaning Virginia, North Carolina, South Carolina, Georgia, Florida, Kentucky, Tennessee, Alabama, and Mississippi). The specific target was to spur the development of community solar at these utilities throughout the Southeast such that at least 200 MW of community-scale solar would be developed by 2020. In order to reach this goal the project team first aimed to develop useful materials and conduct outreach with utilities and other relevant stakeholders. The team then conducted technical assistance projects to help individual utilities evaluate and, in several cases, pursue development of projects. The team conducted nine technical assistance projects in total: five in North Carolina, two in Virginia, one in Georgia, and one in Kentucky. The team also responded to smaller scale information requests from southeastern utilities throughout the project period.

14 SOLAR ENERGY↗

DOE OSTI2020

World Congress on High Entropy Alloys (HEA 2019) (Final Technical Report)

The World Congress on High Entropy Alloys (HEA 2019) was a new, cross-disciplinary technical forum designed to share the latest research advances in materials with high configurational entropy, including both single-phase and multiphase (compositionally complex) alloys. This inaugural World Congress on High Entropy Alloys (HEA 2019) was held in Seattle, Washington from November 17-20, 2019 with the goal of HEA 2019 to assemble the international community of HEA stakeholders – including researchers, educators, and engineers – to capture the current state-of-the-art, identify current gaps in HEA efforts, and to set the stage for the future growth and application of HEAs worldwide. HEA 2019 was the environment for leaders in this field to showcase their researc, and network with their peers to informally discuss the latest developments in high entropy alloys, while also making valuable professional connections. The goal of the organizers was to ensure a high-quality conference that held a strong international presence and aimed to highlight the important advances in HEA research on a global scale. Student participation was greatly encouraged in order to give students exposure to recent advances in this field. This meeting was open to all interested individuals and attempted to provide the most advanced technical meeting possible, with a mixture of attendees from research and development, industry, and education.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Developing Metrics to Evaluate the Skill and Credibility of Downscaling (Final Report)

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Tribal Renewable Energy: Bishop Paiute Tribe, Residential Solar Program Phase II (Final Report)

The project consisted of the design, installation, inspection, and interconnection of 35 grid-tied, solar electric systems, totaled 123 kW rated capacity, on qualified existing low-income single-family homes located within the Bishop Paiute Reservation, which provide at least 65-79% savings in displaced electricity. Tribal job trainees were hired for each installation, gaining valuable job experience. Additionally, each homeowner was educated on energy efficiency and renewable energy. The overall project goal was to deploy clean energy systems in order to achieve the Bishop Paiute Tribe’s long-term goals of energy self-sufficiency, environmental protection, and better lives for our Tribal members and community. The energy displaced was 82.4 percent of total electricity used (exceeding estimated 65-79%)or over 170,000 kWh/year generating approximately $1.29 million worth of power for low-income families over their lifespans, while eliminating an estimated 2,640 tons of greenhouse gas emissions. This reduction makes a significant difference on the reservation giving more families money to spend on other essential items, while reducing their carbon footprint in this beautiful mountain community. Also, implementing these 35 systems provided a approximately 132 hours of paid solar installation work for tribal members. Training and good paying jobs are scarce on the reservation and solar is the fastest growing industry in CA and this training offered our members a real chance to learn and then get paid. The program is very significant to the family who qualified, as most families fall below the federal poverty guidelines, and many are living paycheck to paycheck. Overall, the triple impact of the Bishop Paiute Tribe Residential Solar Program Phase II— affordable energy for low-income families, on-site clean energy production, and hands-on solar installation jobs for local workers—these all help build the Tribe’s energy, economic, environmental, and social self-sufficiency and sovereignty amongst the most needy on the Reservation

14 SOLAR ENERGY↗

DOE OSTI2020

30 cm Drop Modeling

This report documents modeling and analysis of the 30 cm cask drop scenario for spent nuclear fuel (SNF) casks. The 30 cm drop is an important hypothetical dynamic loading scenario for SNF because 10 CFR 71.71 defines testing requirements for normal conditions of transport (NCT) of SNF packages, and free drop (of 30 cm for the heaviest packages) tests are required. Other NCT conditions specified in 10 CFR 71.71 include vibration normally incident to transport, and DOE’s multimodal transportation test (MMTT) and related analysis concluded that mechanical shock and vibration incident to transportation is negligible for SNF structural integrity because the loads are so small. The SNF cask 30 cm drop has a lot more potential to cause damage to SNF because the kinetic energy and momentum of the system is stopped abruptly during the cask impact event. Test data and model predictions both agree that the SNF assemblies are subjected to significantly higher loads in a cask drop event than normal transportation shock and vibration, but currently there is no reason to expect gross structural damage of the fuel assembly or widespread SNF cladding failure as a result of a 30 cm cask drop. The ultimate goal of this work is to close the knowledge gap of stress profiles on SNF rods and fuel assembly components during NCT, and this report describes the progress toward reaching that goal as well as a plan for finishing this work over the next year or two. Key remaining tasks include refining the fuel assembly model, calculating a selection of specific fuel assembly cases to populate the damage model, and finally running the damage model to predict the full general response range of 30 cm drop loads on SNF.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Handheld Biosensor for COVID-19 Screening

We have made significant progress toward the development of an integrated nucleic acid amplification system for Autonomous Medical Devices Incorporated (AMDIs) Optikus handheld diagnostic device. In this effort, we developed a set of loop-mediated isothermal amplification (LAMP) primers for SARS-CoV-2 and then demonstrate amplification directly on a surface acoustic wave (SAW) sensor. We built associated hardware and developed a C-code to control the amplification process. The goal of this project was to develop a nucleic amplification assay that is compatible with SAW sensors to enable both nucleic and serological testing in a single handheld diagnostic device. Toward this goal, AMDI is collaborating Sandia National Laboratories to develop a rapid, portable diagnostic screening device that utilizes Sandias unique surface acoustic wave biosensor (SAW) for COVID-19 detection. Previously, the SANDIA- AMDI SAW sensor has successfully detected multiple high-profile bacteria viruses, including Ebola, HIV, Sin Nombre, and Anthrax. Over the last two years, AMDI and SANDIA have significantly improved the sensitivity and detection capability of the SAW biosensor and have also developed a modular hand-held, portable platform called the Optikus, which uses CD microfluidics and handheld instrumentation to automate all sample preparation, reagent introduction, sample delivery, and measurement for a number of different assay targets. We propose to use this platform for the development of a rapid (%3C30 minutes), point-of-care diagnostic test for detection of COVID-19 from nasal swab samples.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Reification of latent microstructures: On supervised unsupervised and semi-supervised deep learning applications for microstructures in materials informatics

Machine learning (ML), including deep learning (DL), has become increasingly popular in the last few years due to its continually outstanding performance. In this context, we apply machine learning techniques to "learn" the microstructure using both supervised and unsupervised DL techniques. In particular, we focus (1) on the localization problem bridging (micro)structure (localized) property using supervised DL and (2) on the microstructure reconstruction problem in latent space using unsupervised DL. The goal of supervised and semi-supervised DL is to replace crystal plasticity finite element model (CPFEM) that maps from (micro)structure (localized) property, and implicitly the (micro)structure (homogenized) property relationships, while the goal of unsupervised DL is (1) to represent high-dimensional microstructure images in a non-linear low-dimensional manifold, and (2) to discover a way to interpolate microstructures via latent space associating with latent microstructure variables. At the heart of this report is the applications of several common DL architectures, including convolutional neural networks (CNN), autoencoder (AE), and generative adversarial network (GAN), to multiple microstructure datasets, and the quest of neural architecture search for optimal DL architectures.

36 MATERIALS SCIENCE↗

DOE OSTI2020

China’s Bid To Lead Artificial Intelligence Chip Development within the Decade

In 2017, the Chinese government announced an ambitious, broad strategy to become the global leader in artificial intelligence (AI) theories, technologies, and applications by 2030 and indicated that China’s ability to indigenously produce cutting-edge AI chips would be integral to its success. China’s goal to become a dominant producer of AI hardware within a decade is a bold undertaking because China faces domestic chip production challenges and fierce competition from US chip producers. Our review of Chinese AI chip product lines shows various levels where Chinese companies compete with global firms in the production chain. China lacks a robust indigenous AI chip production infrastructure, and the United States and its allies are tightening controls on the supply of advanced semiconductor manufacturing equipment (SME) and electronic design automation (EDA) software to China. In contrast to their Chinese counterparts, US companies operate in all areas of AI chip production and have consistently driven the development of new chip designs. AI chip production is a costly endeavor, and China’s chip producers currently lack the customer base to lead global AI chip development by the 2030 goal. An expanded customer base may help China attract the necessary expertise to bolster its AI chip production chain. This would also help Chinese producers make their investments in the requisite technology economically sustainable. Chinese researchers continue to pursue promising next-generation AI chip designs, such as neuromorphic computing-based architectures, which in the next five to ten years could position Chinese companies to make or contribute to key innovations in the field.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2020

Systems Level Understanding of Interconnected Methane and Nitrogen Cycles Using Complex Synthetic Communities

The main goal of this project was to follow up on prior discovery of the communal nature of methane utilization by the aerobic methanotrophic bacteria, resulting in carbon transfer along a food chain. This goal was approached via manipulation of specially designed, synthetic bacterial communities, fed exclusively by methane, under a variety of simulated environmental conditions. Using (meta)genomics, metatranscriptomics, stable isotope probing and mutant generation, we obtained solid evidence for the nature of the core microbiota involved in collaborative methane consumption, the major players (true methanotrophs) being the members of the family Methylococcaceae, their major partners (non-methanotrophic methylotrophs) being members of the family Methylophilaceae, and minor but persistent partners in the communities being members of the orders Burkholderiales and Bacteroidetes. Metabolic reconstruction from single genomes and metagenome-assembled genomes (MAGs), along with metatranscriptomics results delineated major pathways for carbon metabolism, suggesting that the methanotrophs share different organic compounds with different functional guilds: methanol with Methylophilaceae, acetate with Burkholderiales, and polymeric substances with Bacteroidetes. Overall, the results of this project expand our understanding of microbial metabolism of methane and, thus, provide basis for strategies for microbial methane mitigation, with obvious benefits to the society of the United States and worldwide.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Monolithic Spatial Heterodyne Raman Spectrometers (mSHRS): Toward highly miniature chemical sensors for deployment on moving platforms (Final Report, Phase I)

This report covers phase 1 (year 1) of the mSHRS project. Our ultimate long-term goal is to develop highly miniature Raman analyzers, known as spatial heterodyne Raman spectrometers (SHRS), that are deployable as in-situ chemical sensors on moving platforms. During Phase I (FY19/20) funding, our team focused our efforts solely on the key innovation needed toward realizing that goal: the development of the monolithic interferometer comprising the beam splitter and gratings with the appropriate design parameters and tolerances to enable Raman interferometry. We successfully developed and characterized the performance of the first monolithic SHRS devices including a monolithic version that incorporates field-widened optics. Our solid-state design approach integrated all optical components as a single monolithic unit for maintaining precise optical alignment during sensor operation, a requirement for operating in a vibration prone environment. This project has two principle activities: (1) Design and fabricate monolithic SHRS devices (i.e. monolithic device task) and (2) characterize the mSHRS devices in terms of performance (i.e. the Monolithic SHRS characterization task).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

Better Plants Resources for Achieving Science Based Targets

The US Department of Energy’s (DOE’s) Better Buildings, Better Plants Program is a voluntary initiative that works with leading manufacturers to showcase leadership and drive deep energy savings in the U.S. industrial sector. Partners agree to set ambitious sustainability goals and in return receive robust technical assistance, national recognition, facilitated peer-to-peer learning opportunities, and access to innovation. Many Better Plants partners are looking to translate their energy intensity progress towards carbon reduction goals and exploring if setting a Science-Based Target (SBT) is right for their organization. This document provides an overview of the SBT initiative and compares it to the offerings of the Better Plants program. To help companies who are participating in both initiatives, DOE tools and resources are highlighted and discussed.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Use of Remote Sensing and In-Situ Observations to Develop and Evaluate Improved Representations of Convection and Clouds for the ACME Model

The overachieving goal of the whole CMDV-MCS project is to improve understanding of warm season continental convection and to develop treatments of convection and microphysics capable of representing mesoscale convective systems (MCSs) features in large-scale models. Our tasks for this project contributing to the overachieving goal include: (1) Improve the ice nucleation formulation for MG2 and P3 cloud microphysics schemes; (2) Improve the treatment of subgrid dynamics and thermodynamics driving the ice nucleation in E3SM; and (3) Test the performance of improved ice microphysics in E3SM with observation data. In this project, we have (1) Improved the ice nucleation parameterization for MG2 and P3 in E3SM by implementing two advanced empirical parameterizations with connection to aerosols. The two deterministic heterogeneous ice nucleation parameterizations (i.e., DeMott et al., 2015; Niemand et al., 2012) were merged with the MG2 and P3 cloud microphysics schemes in E3SM. Long-term simulations were conducted to examine the impacts of these new parameterizations on simulated cloud properties; (2) Improved the treatment of subgrid dynamics and thermodynamics driving the ice nucleation in E3SM. We evaluated the double Gaussian PDF of vertical velocity simulated by the Cloud Layers Unified By Binormals (CLUBB) and the sub-column vertical velocity sampled from the Subgrid Importance Latin Hypercube Sampler (SILHS) in E3SM. We introduced the vertical velocity variance induced by topographic gravity waves for ice nucleation and droplet activation; and (3) Tested the performance of improved ice microphysics in E3SM with observation data. We tested the new treatments of ice nucleation in the single column model (SCM) mode for the stratiform mixed-phase clouds observed during 9-10 October 2004 in the DOE ARM Mixed-Phase Arctic Cloud Experiment (M-PACE) and for the convective clouds observed on 20 May 2011 in the Midlatitude Continental Convective Clouds Experiment (MC3E). Modeled ice nucleating particles (INPs) concentrations were compared against observations collected around the globe.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Catalytic Removal of Oxygen and Pollutants in Exhaust Gases from Pressurized Oxy-Combustors

The primary goal of this project was to develop and validate advanced catalytic materials and systems for purifying the flue gas generated from pressurized oxy-combustors in an effort to achieve the purity specifications of carbon dioxide (CO 2 ) streams required by the U.S. Department of Energy (USDOE) for application in enhanced oil recovery. The technology has shown great potential for improving energy efficiency, simplifying process complexity, and lowering costs compared with current state-of-the-art oxy-combustion flue gas purification technologies. Laboratory studies were conducted for the development, characterization, and screening of metal catalysts for residual oxygen (O 2 ) reduction with methane (CH 4 ) and multifunctional carbon catalysts for combined nitrogen oxides (NO x ), sulfur oxides (SO x ), and mercury (Hg) removal. A bench-scale reverse-flow fixed-bed (RFFB) reactor and a trickle-bed direct-contact cooler (DCC) reactor capable of treating 15 standard liters per min of pressurized oxy-combustion flue gas were fabricated and tested with both a simulated flue gas in the laboratory and a slipstream of actual flue gas at a 100 kW th Staged, Pressurized Oxy-Combustion (SPOC) pilot facility. Process simulation and techno-economic studies were performed to evaluate the energy efficiency and cost of the developed catalytic flue gas purification process integrated into a conceptual 550-MWe SPOC power plant. The goal and objectives of the project have been successfully accomplished. A cobalt-manganese (CoMn) oxide catalyst was developed and demonstrated in the bench-scale RFFB reactor in either a reverse-flow or one-direction flow mode of operation that met the success criterion of performance for residual O 2 reduction. A carbon catalyst was developed and demonstrated in the bench-scale DCC reactor that met the success criterion of performance for combined NO x /SO x /Hg removal. Slipstream testing of the integrated DCC-RFFB system at the SPOC pilot facility demonstrated stable operation and verified the superior performance obtained in the laboratory. The techno-economic analysis showed that a 550-MWe SPOC plant integrated with the catalytic flue gas purification process would result in costs of electricity of $\$$96.94/MWh and $\$$80.27/MWh in two assessed cases compared with $\$$91.07/MWh reported for the USDOE’s Current Technology Case, which generated only a partially pure CO 2 stream. On the basis of the results and findings from this project, scale-up studies of materials production and system demonstration and optimization studies of reactors and processes are recommended at the next stage of technology development.

20 FOSSIL-FUELED POWER PLANTS↗