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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.

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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Line emission mapper microcalorimeter spectrometer

The line emission mapper (LEM) is a probe-class mission concept that is designed to detect x-ray emission lines from hot ionized gas (T > 10 6 K) that will enable us to test galaxy evolution theories. It will permit us to study the effects of stellar and black-hole feedback and flows of baryonic matter into and out of galaxies. The key to being able to study the hot gases that are otherwise invisible to current imaging x-ray spectrometers is that the energy resolution is sufficient to use cosmological redshift to separate extragalactic source lines from foreground Milky Way emission. LEM incorporates a large-format microcalorimeter array instrument called the LEM microcalorimeter spectrometer (LMS) with a light-weight x-ray optic with 10” half power diameter angular resolution. The LMS microcalorimeter array has pixels with 15" pixel pitch over a 33' field of view (FOV) optimized for the 0.3 to 2 keV energy band. The central 7' region of the array has an energy resolution of 1.3 eV at 1 keV and the rest of the FOV has 2.5 eV energy resolution at 1 keV. The array will be read out with state-of-the-art time-division multiplexing. We present an overview of the LMS instrument, including details of the entire detection chain, the focal plane assembly, as well as the cooling system and overall mechanical and thermal design. For each of the key technologies, we discuss the current technology readiness level and the plan to advance them to be ready for flight. We also describe the current system design and our estimate for the mass, power, and data rate of the instrument. The design details presented concentrate primarily on the unique aspects of the LMS design compared with prior missions and confirm that the type of microcalorimeter instrument needed for LEM is not only feasible but also technically mature.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Manufacture and testing of biomass-derivable thermosets for wind blade recycling

Wind energy is helping to decarbonize the electrical grid, but wind blades are not recyclable, and current end-of-life management strategies are not sustainable. Here, to address the material recyclability challenges in sustainable energy infrastructure, we introduce scalable biomass-derivable polyester covalent adaptable networks and corresponding fiber-reinforced composites for recyclable wind blade fabrication. Through experimental and computational studies, including vacuum-assisted resin-transfer molding of a 9-meter wind blade prototype, we demonstrate drop-in technological readiness of this material with existing manufacture techniques, superior properties relative to incumbent materials, and practical end-of-life chemical recyclability. Most notable is the counterintuitive creep suppression, outperforming industry state-of-the-art thermosets despite the dynamic cross-link topology. Overall, this report details the many facets of wind blade manufacture, encompassing chemistry, engineering, safety, mechanical analyses, weathering, and chemical recyclability, enabling a realistic path toward biomass-derivable, recyclable wind blades.

17 WIND ENERGY↗
DOE OSTI2020

(Invited) All-Solid-State Batteries Using Li 7 La 3 Zr 2 O 12 Garnet Electrolyte Framework

All-solid-state batteries (ASSB) using LLZO (variants of Li 7 La 3 Zr 2 O 12 ) garnet solid electrolyte with lithium metal anode potentially offer higher energy density and improved safety. Rational design of cell architecture as well as manufacturing scalability are key aspects to consider as the technology readiness level advances. A thick composite cathode layer attached to a thin solid electrolyte layer is desirable to obtain superior energy densities. Furthermore, the architecture within the composite cathode may be engineered to contain directional conduction paths of lithium ions or electrons for enhanced rate capabilities. Here, we demonstrate a functioning bulk-type LLZO based all-solid-state battery with a practical form factor incorporating the above described design concepts. Freeze-tape-casting (FTC), a scalable and environmentally friendly ceramic processing method, is used to construct 3D porous LLZO scaffolds composed of vertical arrays of LLZO walls. The thin solid-electrolyte layer is fabricated by tape-casting (TC). By sintering the stacks of FTC and TC green tapes, porous/dense bilayers and porous/dense/porous trilayers of LLZO frameworks are obtained. An ASSB was constructed using a porous/dense bilayer by infiltrating LiNi 0.6 Mn 0.2 Co 0.2 O 2 cathode powder and carbon black into the porous layer and adhering lithium metal foil to the dense side. We find it crucial to introduce a plastic crystal based soft solid electrolyte to the porous layer to electrochemically connect all cathode components, obviating the need for co-sintering to establish contact. The soft nature of the plastic crystal based solid-electrolyte may be able to accommodate the volume change of the cathode material as it cycles. In this device, which contained no liquid component, the initial discharge capacities were similar to those observed in a lithium ion battery configuration using the same cathode powder at C/10 rates.

25 ENERGY STORAGE↗
DOE OSTI2020

Spatial Atomic Layer Deposition to Scale Manufacturing of Robust Catalysts for Biomass Conversion Applications: Cooperative Research and Development Final Report, CRADA Number CRD-17-715

This CRADA will facilitate technology maturation for NREL-developed ALD-coated catalyst materials that are tailored for durability during harsh biomass conversion chemistries. This project will address optimizing process parameters for scale-up of Al2O3 ALD-coated catalysts, demonstrating ALD-coated catalyst performance for muconic acid hydrogenation, and validating economic models that project significant cost benefits for ALD-enhanced catalytic processes. This work will strengthen private-public partnerships in the area of advanced catalyst manufacturing for energy-related technology. Critical information will be collected to elevate the Technology Readiness Level and increase our competitiveness for cooperative R&D agreements and licensing. Success of this work will be crosscutting as it can facilitate advanced catalyst development for both renewable and conventional processes.

09 BIOMASS FUELS↗
DOE OSTI2020

Building a CO 2 Economy in the Four Corners Region [Script plus Slides]

This project will assess options in the Four Corners region relative to developing a CO₂-based economy, considering both CO₂ supply (via capture) and CO₂ demand (utilization and storage). The assessment will consider a spectrum of opportunities at various stages of technology readiness, including their magnitude and regional distribution. An additional component (via a collaboration TBD) will evaluate the regional implications relative to economy and job growth.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Final Report For Project TCF-18-15778

This report documents work performed under the Technology Commercialization Fund (TCF-18-15778, Used (spent) nuclear fuel management and analysis tool) award provided by the US Department of Energy (DOE) Office of Technology Transitions (OTT). This report describes various Used Nuclear Fuel-Storage, Transportation & Disposal Analysis Resource and Data System (UNF-ST&DARDS) enhancements to advance the technology readiness level (TRL). The principal work performed under TCF is the integration of the initial dry storage loading optimization algorithm into UNF-ST&DARDS.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Microwave Cast Material Examination

Microwave-cast material dating from the latest prototype development period and subsequent TRL 7 advancement testing was sent to LANL for additional characterization. The initial characterization described here is considered a supplement to and verification of that performed by Y-12 during the Technology Readiness Assessment process. The carbon chemistry results from Y-12 and LANL regarding early prototype microwave cast test object (CTO) and cylinder castings match within expectations. Only one fully intact as-cast CTO was available for examination in which carbon chemistry does not appear to vary spatially, at least at relatively low carbon levels (hypoeutectic). The large as-cast grain size leads to relatively poor grain size statistics and similar difficulties were encountered during the TRA. Small, isolated gas pores were observed in four of the five metallographic samples in prototype CTO casting PT-01. Finally, the next phase of characterization work, which focuses on corrosion behavior, has started and is described briefly.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Continuous Monitoring and Partial Water Softening for Cooling Tower Water Treatment

Cooling towers are an integral component of many refrigeration systems, providing comfort or process cooling across a broad range of applications. They are the point in the system where heat is dissipated to the atmosphere through the evaporative cooling process. Cooling towers are commonly found in industrial applications and are also often used in water-cooled chilled water plants in medium to large commercial buildings. Continuous monitoring and partial water softening for cooling towers used in medium to large commercial buildings are the focus of this paper. Cooling towers consume large amounts of water. Cooling tower-related water consumption is one of largest potable water loads within buildings in the United States, with substantial building water use associated with heating and cooling. Regional water shortages have highlighted a need to reduce water consumption; the U.S. General Services Administration (GSA) and Executive Order 13834 place priority on reducing water consumption. This priority has fueled interest in the identification, investigation, and potential broad deployment of cost-effective opportunities to reduce water use, such as alternative water treatment (AWT) technologies for cooling towers. Traditional water treatment approaches use chemicals to extend the ability of the water to hold scaling minerals in suspension, minimize corrosion, and prevent biological growth. This treatment protects the chillers and cooling tower equipment; however, even when chemicals are used regularly, a certain percentage of condenser water must be drained and made up with fresh water to maintain system water quality parameters. In addition, the use of chemicals sometimes creates a waste disposal issue and can cause building owners to incur additional fees, such as disposal or wastewater charges. To manage cooling tower water treatment, GSA typically contracts with a company specializing in conventional chemical maintenance for a fixed fee. While there are many types and vendors of AWT systems, this project assesses the effectiveness of one technology provided by Aqualogix. This system is a chilled water plant monitoring and control system aimed at optimizing system performance by reducing the blowdown occurrences used to remove mineral build-up. The technology consists of two components – continuous programmable logic control (PLC) monitoring and side-stream filtration with partial water softening. PLC monitoring calculates cycles of concentration (CoC) and determines the optimum amount of blowdown water required to satisfy all water chemistry requirements. Side-stream filtration removes suspended matter and improves biocide efficacy while precisely dispensing softened water to achieve optimal makeup water hardness. Unlike other AWT systems evaluated by GSA to date, this system does not replace the legacy treatment system but is used in addition to chemical water treatment. The vendor claims their technology will reduce water consumption, water discharge, and maintenance costs. The AWT system evaluated in this demonstration is a commercialized technology. Given its commercialized state, the system evaluated in this report is at a Technology Readiness Level 9 according to National Aeronautics and Space Administration (NASA) definitions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Materials for Harsh Environments

The 2020 Materials for Harsh Service Conditions (M4HSC) Workshop was coordinated by three different U.S. Department of Energy (DOE) Offices: the Advanced Manufacturing Office (AMO), the Office of Fossil Energy (FE), and the Office of Nuclear Energy (NE). The event was held virtually October 27–30, 2020. The workshop brought together stakeholders from academia, industry, national laboratories, and DOE offices to identify the opportunities (paths for obtaining desirable goals), challenges (actionable tasks taken up along these paths), barriers (obstacles impeding advancement along the paths), and research and development (R&D) needs for enabling development of technology readiness level (TRL) 3–6 materials and materials systems, as well as their advancement into widespread commercial application.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

An Economics-by-Design Approach Applied to a Heat Pipe Microreactor Concept

Microreactors present a potential paradigm shift in the nuclear industry. Emphasis thus far has been on large-scale multi-billion-dollar projects that cater solely to grid electricity market. These projects can be challenging to finance and execute. On the other hand, microreactors are intended to target a wide variety of smaller niche markets and are expected to be factory-fabricated and more readily deployable. While diseconomies of scale for microreactors may tend to raise their costs per energy output (MWh) relative to large nuclear plants, offsetting gains can be expected from standardization, simplification, passive safety, lower radionuclide inventories, factory fabrication, fast installation, and low financing costs. To adequately assess these contributions, designers should have a different perspective on cost drivers than for large nuclear plants and can utilize novel approaches for systematic cost reduction. To account for these important aspects of microreactors, this report proposes an economics-by-design approach that places economic considerations at the center of the design process. The methodology builds on existing frameworks such as design-to-cost and value engineering, expanding them to new markets (beyond the grid), new attributes (beyond costs alone), and introducing the approach at earlier points in the design cycle. Design parameters and technical specifications are systematically evaluated until costs meet market entry points, while also providing the high-priority performance attributes of the particular use case. Determining first-order estimates for different components early in the process enables designers to focus R&D efforts on the biggest overall cost contributors and components with the most cost uncertainty. The analysis is always guided by market needs and threshold prices. In addition to microreactors, the approach is expected to be useful for other classes of nuclear reactors as well. The analysis was applied to a concept found in the open literature (the Design A heat-pipe reactor). A comprehensive bottom-up estimate was generated by leveraging a new microreactor-specific code of accounts and a range of cost equations. The initial estimate for levelized cost of electricity (LCOE) unsurprisingly exceeded market ranges since the use case had prioritized technological readiness over economic considerations in design choices. An alternate concept was then proposed, with various assumptions/targets made to reduce the largest cost contributors. Changes in the neutron spectrum, the power output, and building structures were found to make even the first-of-a-kind of this modified concept competitive with diesel generation in some remote communities. Learning rate (LR) assumptions indicated cost reductions achieved from sequential unit deployments could expand the range of competitiveness to include additional markets as deployments proceed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

STEP Report on Advanced ODS FeCrAl Alloys for Fission Applications

Oak Ridge National Laboratory is developing advanced low-Cr oxide dispersion strengthened (ODS) FeCrAl alloys for accident tolerant fuel (ATF) cladding. This report presents the characterization of two new ODS FeCrAl tubes by using powder commercially mechanically alloyed by Zoz GmbH, which underwent high-precision tube rolling with two different annealing schedules. This work shows that the ODS FeCrAl tube without recrystallization exhibits consistent mechanical behavior in comparison with a previously produced tube. The second tube, which underwent a full recrystallization step before the final tube rolling step, showed some circumferential cracking and exhibited limited ductility in the axial tube tensile tests. Based on current and prior work on the ODS FeCrAl alloy system, this report compares the current state of the scientific literature on the alloy class with that of wrought FeCrAl without oxide additions. Then, this report makes recommendations for future research directions that should be undertaken to increase the technology readiness level for ODS FeCrAl as a viable ATF candidate material. This report has been submitted as fulfillment of milestone M3FT-20OR020202064 titled, “STEP Report on Advanced ODS FeCrAl Alloys for Fission Applications” for the US Department of Energy Office of Nuclear Energy’s Advanced Fuel Campaign of the Fuel Cycle R&D program.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Hybrid Analytics Solution to Improve Coal Power Plant Operations

This project focused on developing advanced methods for thermal performance monitoring of a coal-fueled power plant. The specific goal was to develop and demonstrate a new thermal performance monitoring approach using a hybrid model that integrates a physics-based heat balance model with a machine learning-based pattern recognition model. The hybrid model enables increased accuracy and scope of the thermal analysis and an improved ability to monitor and detect changes in plant operation. This new approach takes full advantage of the individual model capabilities and creates an important new set of capabilities not previously possible using the two types of models separately. Using the heat balance model, a rich set of derived parameters (virtual sensors) are calculated from the measured plant operating data at each time point. The combined measured and derived data values are used by machine learning algorithms to create pattern recognition models over the range of normal unit operation. To create the monitoring models, historical data from normal operation of the plant is first processed by the heat balance model to compute the derived parameter data. The result is a greatly expanded set of normal operating data that can be used as input to create the pattern recognition model. Once the models are calibrated for normal operation, the hybrid model is suitable for use in continuous online monitoring. During online monitoring, new plant operating data is processed first by the heat balance model and then by the pattern recognition model. Results from the pattern recognition model quantify the deviation of each measured or derived parameter from its expected value in normal operation. The hybrid models can detect abnormal changes in plant operating data with very high accuracy and sensitivity. When abnormal behavior is detected, alerts are generated automatically for evaluation by the plant monitoring staff. The new hybrid solution product was developed and verified in the performance of the project. The hybrid solution was tested first in a simulation environment that mimicked the plant data systems and infrastructure used by U.S. power generating plants and utilities. The hybrid solution was then deployed for real-time, online monitoring of an operating coal-fueled power plant at a field test site. Field testing demonstrated that all hybrid solution development objectives were accomplished. The project work was based on combining the capabilities of two existing software products to create the new hybrid solution product. One of these was the existing MapEx® heat balance product and the other was the existing SureSense® advanced pattern recognition product. Each of these separate products was assessed to be at a Technology Readiness Level (TRL) of 9 at the start of the effort. The hybrid solution product was assessed to be at a TRL of 2 at the start of the project based on early feasibility work by the project team. At completion of the field testing performed in the project, the hybrid solution product was assessed to be at a TRL of 7. The project team expects that the hybrid solution product will be deployed commercially and will achieve a TRL of 9 within one year after completion of the project.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Auto Indexer for Percussive Hammers Final Report

Geothermal energy has been underutilized in the U.S., primarily due to the high cost of drilling in the harsh environments encountered during the development of geothermal resources. Drilling depths can approach 5,000 m with temperatures reaching 170 C. In situ geothermal fluids are up to ten times more saline than seawater and highly corrosive, and hard rock formations often exceed 240 MPa compressive strength. This combination of extreme conditions pushes the limits of most conventional drilling equipment. Furthermore, enhanced geothermal systems are expected to reach depths of 10,000 m and temperatures more than 300 °C. To address these drilling challenges, Sandia developed a proof-of-concept tool called the auto indexer under an annual operating plan task funded by the Geothermal Technologies Program (GTP) of the U.S. Department of Energy Geothermal Technologies Office. The auto indexer is a relatively simple, elastomer-free motor that was shown previously to be compatible with pneumatic hammers in bench-top testing. Pneumatic hammers can improve penetration rates and potentially reduce drilling costs when deployed in appropriate conditions. The current effort, also funded by DOE GTP, increased the technology readiness level of the auto indexer, producing a scaled prototype for drilling larger diameter boreholes using pneumatic hammers. The results presented herein include design details, modeling and simulation results, and testing results, as well as background on percussive hammers and downhole rotation.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Deep Analysis Net with Causal Embedding for Coal-fired Power Plant Fault Detection and Diagnosis (DANCE4CFDD)

Fault detection and diagnosis is critical to power plant operation to ensure attaining high reliability while reducing operation cost. As more renewable power is introduced to the power grid, traditional fossil power plants take on the extra burden of excessive load cycling to compensate the generation variability from renewable power. Such load cycling will pose more reliability challenges to power plant operation. There are a number of challenges faced by today’s asset health management system in coal- fired (or gas) power plants: 1) high-dimensional nonlinear interaction among multiple time series measurements; 2) high measurement variance induced by operational conditions/modes; 3) variation among asset types and plant configurations; and 4) a small number of faulty events to learn from. To cope with these challenges, today’s fielded asset health management systems rely heavily on manual efforts from domain experts and hand-crafted features or rules based on domain knowledge. Despite its role in plant reliability, such a practice is costly and hinders its scalability and sustainability, particularly when a plant undergoes modifications. The objective of this project is to develop a novel end-to-end AI learning system that is trainable (i.e., the AI representation of a complex system behavior can be directly learned from properly labeled data) for accurate fault detection and root cause analysis. The ability to create a fault detection model directly from time series could alleviate the efforts associated with today’s asset management solution development. In the course of this project, we have achieved the following: Created an AI model development environment incorporating state-of-the-art neural network architectures for rapid model development and evaluation; Developed novel learning strategies for training of fault detection model; Developed special-purpose neural network architecture embedded with variable association graph aiming for better interpretability; Developed a learning strategy to leverage a small number of faulty events for enhanced fault detection capability; Conducted detailed experimental study based on public benchmark datasets and demonstrated the effectiveness of the proposed solution; and Validated the developed system with data from both a coal-fired plant boiler dynamic simulation model and real-world coal-fired power plant covering multiple asset and fault types. Overall, the project attained a technology readiness level of TRL 5 from TRL 2 at the beginning of the project.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

A Novel Process for Converting Coal to High-Value Polyurethane Products

Battelle has demonstrated a patented process for making high-value, polyurethane (PU) foam from coal, based on preparing liquefied coal via direct liquefaction, converting it to polyols as an intermediate via ozonation, and then making PU foams from these polyols. This process represents a breakthrough in innovative utilization of U.S. coals, and is applicable to bituminous as well as sub-bituminous coals. The resulting PU foam products are projected to have an extremely high value (i.e., over $\$5,000$ /ton), with nearly 100% of carbon utilization from coalderived liquid feedstock, and 31.5% to 43.5% of the carbon in the PU foam polyol product being bio-based. The targeted products represent an extremely large (i.e., over $80 billion/year), existing PU foam market, which could expand into making coatings and adhesives. The process can further help reduce petroleum imports, while improving the economics of PU foam production. This work was completed with funding from the National Energy Technology Laboratory (NETL), with cost share from the State of Ohio’s Ohio Development Services Agency (ODSA) and others, and has advanced the process to 10 kg/day continuous scale and thus to Technology Readiness Level (TRL) 5. A total of 48 coal-based polyols were prepared and evaluated. The initial 28 polyols focused on range finding for ideal conditions. The later 20 polyols were produced as part of process optimizations. These optimizations were targeted around a continuous ozonolysis process to evaluate extended time reactions and to create the necessary intermediate for production of 1-gallon samples of polyol. The most unique attribute of Battelle’s polyol is in the utilization of coal’s aromaticity to gain final foam rigidity. Typically, polyols depend on the isocyanate fraction and cross-linking to gain rigidity. By utilizing coal, we were able to maintain rigidity while reducing the overall hydroxyl value of the polyol. This is important as lower hydroxyl value leads to greater percent weight of the coal-based polyol because less isocyanate is required for foaming. This leads to greater foam cost savings. This report provides the details, process, and process cost models of the conversion of coal to polyols and further to PU foams. Battelle’s process begins with coal liquids. These liquids can be obtained by two processes: coal coking or pyrolysis to produce coal tar, and Battelle’s biobased coal-to-liquids (CTL) process to produce heavy syncrude after liquifying >85% coal. After liquification, Battelle utilizes ozonolysis to create functionalization on the polyaromatic coal structure. The functionalization is then converted to the final polyester polyol through transesterification, or to hydroxyamide polyol through amidification. Equivalent or better standard properties have been obtained for 2 lb/ft 3 density rigid, water and freon-alternative blown foams, including compressive strength, density, R-value, and dimensional stability. Target applications for these foams are insulation, packaging, and energy-absorbing foams. Some exploratory testing also showed promise for adhesives applications. A detailed economic analysis showed that Battelle’s polyol process is economical, at a 140 metric tons per day (MTD) polyol production scale. An attractive return on investment (ROI) at competitive pricing validates the process is ready for a pilot-plant demonstration. A scale-up plan is provided.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Micro-Environmental Control System (Final Report)

This project developed an innovative micro-environmental control system (µX) that enables office buildings to reduce energy used for heating and cooling by 15% or more. The µX is a compact, quiet, and ergonomic device that is designed to be installed under an office workstation; it is designed to maintain occupant comfort when room thermostat setpoints are incremented by 4°F or more (warmer in the summer and cooler in the winter) to save energy. When ambient room temperatures are outside of the usual comfort range, the µX maintains occupant comfort by delivering personalized cooling or heating locally to each office worker. The µX provides personalized cooling using a micro vapor compression system that includes a new high-performance micro-scroll compressor and a novel thermal storage unit. The vapor compression system operates at night to freeze a phase-change material (PCM). During the workday, the cooling stored in the PCM is released as a cool breeze of air to make occupants more comfortable. The micro-scroll compressor was developed specifically for this application; it is smaller than any of its type, minimizing the amount of power needed. In heating mode, the µX maintains occupant comfort using a foot heating mat with an infrared reflective box. The µX R&D project was conducted by Syracuse University in collaboration with United Technologies Research Center, Air Innovations, Bush Technical, and Cornell University. Over the course of the initial three-year project, the team developed and evaluated four versions of the unit, advancing the concept to Technology Readiness Level 6. The capabilities of individual proof-of-concept prototypes were verified in tests that were conducted with: 1) units in psychrometric chambers, 2) an instrumented manikin in a laboratory, and 3) human subjects in laboratories that simulate office environments. The tests verified that the µX prototypes met or exceeded all performance targets required to enable office buildings to reduce energy used for heating and cooling by 15% or more by maintaining occupant comfort when thermostat setpoints are incremented by 4°F or more.

25 ENERGY STORAGE↗
DOE OSTI2022

Advanced Integrated Reticular Sorbent-Coated System to Capture CO 2 from the Atmosphere (AIR2CO2)

GE Research Center (GRC) and the University of California, Berkeley (UCB) executed an 15-month, $1.0 MM program to develop a lab-scale material system to extract CO 2 from ambient air using UCB’s pioneering sorbent technology and GRC’s composite coating expertise. The primary objective of this project was to develop an “Advanced Integrated Reticular Sorbent-Coated System to Capture CO 2 from the Atmosphere (AIR2CO2)” at a Technology Readiness Level (TRL) of 3. The AIR2CO2 concept relies on two key innovations: 1) advanced sorbent architectures with high capacity and rapid sorption kinetics that enable effective CO 2 capture at low concentrations, and 2) tailored MOF-binder slurry formulations and coating processes that enable sorbent integration into a novel additively-manufactured contactor.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Dynamic Decarbonization through Autonomous Physics-Centric Deep Learning and Optimization of Building Operations (Abstract only)

This project directly addresses the primary goal of Area of Interest 2 in the CRADA call: to advance optimization-based integrated energy management systems in commercial and residential buildings. Pacific Northwest National Laboratory (PNNL) and its industry partner PassiveLogic aim to accomplish this by reaching three key objectives. First, to ensure a broad impact in the building controls industry, PNNL will extend its open-source library for predictive control synthesis by augmenting its capabilities with data-driven self-learning of building models and auto-calibration of predictive controllers. The effort will focus on building use cases selected in collaboration with PassiveLogic. The team will specifically address the development of methods for data-driven adaptation of building models, investigation of model architectures that best address specific building types, and automated synthesis of differentiable predictive controllers that optimize diverse objectives. Second, PNNL will collaborate with PassiveLogic to integrate the aforementioned methods with PasiveLogic’s advanced controls platform. The collaborative integration effort will inform the developments under the first objective by providing specific data on the attainable performance of model learning on resource-constrained edge computing platforms. This software integration effort will increase the technical maturity of the developed libraries by exploring the use of software integration tools and methods. Third, PNNL and PassiveLogic will work to improve the technology readiness of the developed predictive controllers by testing their performance in relevant test environments, such as high-fidelity simulation, hardware in the loop, and actual test buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗