Fiscal Year 2024 CLIMR Projects: Transforming Clean Energy Technologies (2024)

AI Technology Licensing Accelerator Solution (ATLAS)

Partnering labs: NREL, ORNL, LLNL, SNL, BNL, SRNL, LANL

AI Technology Licensing Accelerator Solution (ATLAS) is a two-year project to demonstrate the application of artificial intelligence (AI) in technology transfer. It will generate valuable methods and applications that will be shared across all Department of Energy (DOE) labs to enhance productivity and licensing numbers.

National Laboratory Licensing Playbook

Partnering labs: INL, PNNL, LLNL, PPPL, SNL, ANL

Technology licensing is essential to how the U.S. Department of Energy’s (DOE) national laboratories transition innovative technologies to the private sector. Sophisticated and consistent licensing practices across each national laboratory technology transfer office (TTO) serves to protect DOE-funded intellectual assets for national and economic security and to encourage domestic supply chains while also accelerating the transfer of promising energy technologies to the private sector for effective commercialization and impact. This TCF project proposes the development of a “Licensing Playbook” as a professional resource for licensing practitioners across the community of DOE national laboratory TTOs. The guidance provided in the Licensing Playbook will include detailed explanations of the intent of several key patent license agreement provisions, professionally accepted standards of practice, statutory or prime contract bases for requirements and references to relevant case law impacting the construction and application of each agreement provision. Negotiated alternatives for each provision would then be sourced from national lab TTO licensing practitioners and then modified to align with the construction of the provision being assessed while removing the identity of the lab contributing content. The Licensing Playbook will serve as a reference for TTO licensing professionals to communicate best practices, highlight risks, and to enable a more standardized approach to licensing laboratory innovations to the private sector.

Network Engagement and Connection with the PIA

Partnering lab: Fermilab

NREL will develop creative solutions and implement a partnership intermediary agreement (PIA) within the national lab structure. This has been done before by a few other labs, but expanding this capability to more labs will advance DOE’s potential mechanisms available to develop agreements with industry. Building this new PIA connection will specifically help develop a pathway that will better enable DOE’s American-Made Network to work with industry partners to advance technologies and commercialization, work with national labs related to vouchers, and build capacity, technical assistance, workforce development programs and more.

Low-Carbon Chemical Synthesis via Mixed Plastic Waste Recycling (Lab Embedded Entrepreneurship Program project)

Our world faces a mounting problem: a significant portion of plastic waste, often existing as a mix of various types, cannot be effectively recycled using traditional mechanical methods due to contamination or limitations in sorting technologies. These mixed plastics end up in landfills, polluting the environment and posing a significant threat to ecosystems. This project proposes a groundbreaking solution: transforming this problematic mixed plastic waste into valuable chemicals. ORNL recently developed a game‐changing technology that can readily depolymerize various plastic types and their wide array of mixed plastic wastes into valuable chemicals. Thus, the primary objective of this project is to mature the technology and develop a scalable chemical recycling system for a variety of mixed plastic wastes. Re‐Du, a Lab Embedded Entrepreneurship Program (LEEP) supported startup, and ORNL aim to leverage ORNL's innovative technology to establish a commercially viable system for recycling mixed plastic wastes. By transforming mixed plastic wastes into valuable resources through a low‐carbon chemical recycling process, the technology can not only address a pressing environmental concern but also establish a more responsible and eco‐friendly approach to chemical production.

Streamlining Lab-to-Market Workflows Phase II

Partnering labs: Fermillab, JLab, LANL, LBNL, NREL, ANL, INL, SNL, SRNL, BNL

This proposal aims to build upon the collaborative efforts of partner Laboratories and partner Salesforce® conducted under “Phase 1” FY22 TCF Base project. This proposed “Phase 2” was anticipated in the Phase 1 proposal and extends the standardization of Technology Transfer workflows and data structures to incorporate Adoption Readiness Level (ARL) analysis directly into the intellectual property evaluation workflow and further extends the agreement workflows to include industry partnership research agreements. This proposal is specifically designed to further accelerate the transition of technology from US National Laboratories into the marketplace. This proposal aligns with the objectives of Topic 5, "Streamlining Processes and/or Requirements," with a focus on streamlining technology adoption readiness and Laboratory collaborations with industry to achieve US economic competitiveness through promising energy-related technologies developed by DOE National Laboratories. It builds on the success of a Phase 1 implementation of normalized workflows for technology transfer for licensing and related industry engagement processes between US FFRDCs and industry. The proposed effort will extend the system to support FFRDC engagements with industry on cutting edge research and development.

Rapid Artificial Intelligence Innovation Cycles for Energy (RAIICE)

Partnering labs: INL, ORNL, Fermilab, BNL, LANL

Rapid Artificial Intelligence Innovation Cycles for Energy (RAIICE) will demonstrate a scalable and easily replicable partnership model designed to reduce the barriers of commercialization and advance transfer of lab-developed artificial intelligence/ machine learning (AI/ML) technologies within the clean energy sector. At the core of every AI/ML system is the need for high-quality datasets used to train the algorithms. There are often barriers to accessing the datasets needed for reliably training AI technologies. This can impede innovation for smaller companies and create challenges to commercializing lab-developed technologies. RAIICE will position the DOE complex to be an accelerator of AI/ML innovation for clean energy advances through compilation of high-quality datasets and create case studies of how startups and small companies can leverage the data to drive new technologies. The RAIICE model will identify key issues in clean energy that can benefit from conceptual AI/ML innovations and compile the correct datasets based on those concepts. While this proposal will not fund technical work needed in the datasets, it will address the compilation and IP needs required for open access. The outputs will be datasets that can be used to further clean energy innovation ultimately boosting US economic strength in this sector.

DOE Boost 2.0 - Inclusive Entrepreneurship and Commercialization and a New Focus on Deployment

Partnering labs: PPPL, LANL, KCNSC, INL, NREL, BNL, JLab

Boost 2.0 is a continuation, improvement and expansion of the successful Boost 1.0 (funded under FY22 TCF) with an emphasis on increasing the market pull phase of the program. Boost 2.0 features the continuation of programming and the creation of several new features that will extend the support to successful alumni companies to better drive participating ventures to commercialization, demonstration and deployment. This includes the creation of the Deployment Partner Network (DPN) which will consist of large industrial firms and venture investors. The DPN members will be involved in helping select regional energy justice challenges and selecting technologies, mentoring participating teams and companies in the cohort and assisting post cohort on the identification and implementation of demonstration plans. Boost 2.0 will continue to provide a crucial service to DOE labs with the goal of commercializing technologies, establishing Cooperative Research and Development Agreement (CRADA) partners and demonstrations.

ACTION: Achieving Net Zero Through Innovative Technology Commercialization

Partnering labs: INL, LANL, NREL, NNSS

Immediate action is needed for the U.S. to meet its climate targets, but there are significant barriers to widespread deployment of new technologies to lower emissions. Achieving Net Zero Through Innovative Technology Commercialization (ACTION) will help achieve the nation’s goal to reduce CO2 emissions to net zero, which is critical to mitigating climate-related disasters. ACTION will build a sustainable, replicable model for commercializing DOE-developed technology by utilizing DOE Net Zero sites as proving grounds for innovative commercial deployments. DOE’s commercial Adoption Readiness Level (ARL) Framework will be utilized to provide a pathway for advancing technologies from system demonstration to first-of-its-kind commercial deployment. Industry technology developers, end users, and community stakeholders will be engaged to define market segments, commercialization barriers, and adoption requirements for lab-developed technologies to achieve net zero emissions. An internship to help advance common DOE goals and initiatives to deploy clean energy technologies to the market and Tribal lands will accompany these activities.

Leveraging SRNL's Advanced Manufacturing Collaborative (AMC) for Commercialization and Innovation

Partnering lab: ORNL

The "AMC Beacon Project'' proposes to utilize the Savannah River National Laboratory's Advanced Manufacturing Collaborative (AMC) to enhance the impact of DOE-funded research and development in commercial sectors. The first year of the initiative will focus on designing, planning, and creating a roadmap to achieve six primary objectives: 1) Facilitating the transition of laboratory technologies to market, 2) Building partnerships with industry for collaboration and technology validation, 3) Boosting public and industry awareness of AMC capabilities, 4) Conducting strategic analysis to identify and exploit emerging opportunities, 5) Developing a robust network to support the AMC ecosystem, and 6) Cultivating a commercialization-centric culture at SRNL. In this initial phase, Beacon aims to lay the groundwork for commercializing AMC technologies, engaging participants in commercialization activities, and reaching out to commercialization ecosystem stakeholders to foster a vibrant entrepreneurial ecosystem at AMC, SRNL, and DOE. The project aligns with DOE and SRNL strategic goals, promoting industry dialogue and enhancing SRNL's presence in the business community.

SolarSnitch: Cyber-Physical, Robust Intrusion Detection and Mitigation for Photovoltaic Inverters

Lead lab: Sandia National Laboratories

To address a significant and emerging gap in power systems cybersecurity, a proactive intrusion detection and mitigation system (PIDMS), renamed SolarSnitch, was developed by Sandia National Laboratories to secure grid-edge photovoltaic (PV) communications in DER systems. SolarSnitch is a distributed, flexible bump-in-the-wire solution for protecting PV smart inverter communications. Both cyber and physical data are automatically processed using deep packet inspection tools and custom machine learning (ML) algorithms to detect abnormal events and to correlate cyber-physical events. For maturing SolarSnitch and readying it for commercialization, further focus on the development of the behavior-based techniques is needed to assess robust performance for a wide array of scenarios and increase detection accuracy. Specifically, ML robustness/assuredness improvements are needed for the SolarSnitch’s adaptive resonance theory artificial neural network (ART-ANN) implementation for detecting abnormal events. There are three focus areas for ML robustness, robustness to common data integrity issues, robustness given the array of possible grid topologies, and robustness given a variety of malicious activity such as data poisoning and other attack scenarios. Therefore, under the proposed DOE TCF project, these ML improvements, flexible software container development, and testing within realistic environments with project utility partners will greatly improve SolarSnitch maturity and deployment readiness.

Commercializing the Orchestration of Networked Microgrids

Lead lab: Oak Ridge National Laboratory

This project proposes to commercialize the Microgrid Orchestrator - foundational control technology enabling networked microgrids - developed by Oak Ridge National Laboratory (ORNL) through partnership with New Sun Road (NSR). Networked microgrids are clusters of co-located, electrically connected, independent microgrids which have the potential of improving reliability, resilience, and economics by sharing resources and coordinated control. The Microgrid Orchestrator is the control layer responsible for coordinating networked microgrids to realize these benefits. NSR is a Public Benefit Corporation with a mission to accelerate communities’ access to renewable energy. Its commercially available Stellar Microgrid OS (MOS)™ cloud-based microgrid control platform is used in over 1,000 microgrids in 22 countries in applications including disaster relief, commercial and agriculture facilities, telecommunications, and community- and utility-owned microgrids. NSR will work with ORNL researchers to incorporate the Microgrid Orchestrator into its Stellar™ platform and validate the control of networked microgrids. NSR will leverage its customer base to execute a commercialization plan consisting of a market assessment of customer types including the regulatory environment, developing a go-to-market strategy, and engaging with prospective customers to secure a target of three paid pilot networked-microgrid projects using the new Microgrid Orchestrator features.

Demonstration of a Traveling Wave-Based Protection Scheme for Distribution Systems with High Penetration of Distributed Energy Resources

Lead lab: Sandia National Laboratories

The project aims to pilot Sandia’s fast fault detection and location prototype using Traveling Waves for power distribution systems. The device will use NuGrid’s optical, high-bandwidth voltage sensors to capture high-frequency fault signatures. The aforementioned equipment will be installed at partner Roosevelt County Electric Cooperative's substation for a two-month demonstration. This project aims to de-risk the most pressing challenges for this technology's viability and eventual commercialization, as identified during the Sandia team’s participation in Energy I-Corps Cohort 17. These challenges include workflow adoption and ease of use, key partnerships, and infrastructure/ delivered cost. With DOE OTT’s TCF funds, the project team will be able to address these risks in the path to market and identify future partnership and commercialization opportunities.

Industrialization and Advancement of the INL RAPID-Microgrid-in-a-Box, Relocatable/Resiliency Alternative Power Improvement for Distribution – Microgrid

Lead lab: Idaho National Laboratory

An in situ grid dynamic driven failure prediction methodology for integrating next-generation power electronics into grid and solar power system

Lead lab: Argonne National Laboratory

In this project, Argonne National Laboratory (Argonne) will partner with Kyma Technologies, a leading GaN power device manufacturer, to validate Argonne’s technology (Argonne invention disclosure #IN-23-096) on in situ grid-dynamic driven failure analysis of next-generation power electronics. This will facilitate the integration of this type of electronics into grid and solar power systems and pave a path for commercializing Argonne’s technology with power electronics manufacturers. Power electronics that are used in power flow controllers and solar power inverters are subject to failure, which is uncertain in nature. Moreover, when it comes to integrating next-generation power electronics into grid-enhancing technologies and solar power systems, these failures are more unpredictable, which severely impacts system reliability and resilience. This project aims to improve power system reliability by demonstrating and validating a methodology for predicting power electronics failure more accurately and efficiently. This will translate module-level grid/ solar dynamic properties to equivalent electrical and thermal stress conditions, then perform in situ failure analysis of power electronics at those stress conditions, and finally develop a prediction model of their performance/ failure reflecting real-time system scenarios.

Resilient, Reliable and Equitable Planning of Microgrid Retrofits in Distribution Systems (REAP)

Lead lab: National Renewable Energy Laboratory

One of the most effective strategies to improving resilience to extreme weather events is through microgrids, where loads, such as hospitals and fire stations, can continue to be supplied electricity through resources situated in proximity even if the distribution grid is out of service due to infrastructure damage. Scaling this approach, however, to each customer in a distribution system for improved resilience-for-all is an enormous task, because of significant initial investment and limited geographical size and installed capacity. Furthermore, at present, microgrid installations at a community level typically do not happen in poor and under-privileged communities, which are mostly left behind from this technological advancement even though they are the population most vulnerable to the consequences of extreme weather events. This project proposes to retrofit electricity distribution systems into community microgrids for resilient, reliable, and socially equitable operation, and deliver as an outcome of the project a commercially viable retrofit planning tool called the Resilient, Reliable and Equitable Planning of Microgrid Retrofits in Distribution Systems (REAP). In this project, NREL is partnered with the software vendor Electric Power Engineers (EPE) and utility partner Colorado Springs Utility (CSU) to achieve the development and integration of the proposed REAP tool.

Seawater battery for long duration grid storage

Lead lab: Oak Ridge National Laboratory

Improving commercial adaptation of DFM and associated RCC processes through development of accelerated stress testing protocols

Lead lab: National Renewable Energy Laboratory

This project will develop accelerated aging protocols to predict the deactivation mechanism of the dual function materials (DFMs) under real-world and long-term operating conditions in reactive carbon capture (RCC) process. These understandings will be utilized to guide DFM design to improve stability and develop regeneration protocols to recover RCC performance of the DFM. The outcome of this project will accelerate the commercial adoption of the RCC technology. In addition, the capabilities and protocols developed in this project will set the foundation for NREL to establish a standardized test bed for RCC technologies and establish collaboration with other research groups working on similar RCC approaches.

Collaborative Approach to Identify Degradation Mechanisms and Validate Aging Protocols for a Diverse Set of DAC Materials

Lead lab: National Energy Technology Laboratory

Partner labs: ORNL, LANL

The U.S. Department of Energy’s Carbon Negative Shot is supporting the development of negative emissions technologies including direct air capture (DAC). Unfortunately, many DAC materials suffer from oxidative, hydrolytic and/or thermal degradation during cycling which can lead to uptake capacity loss and the production of unwanted emissions such as ammonia. In this project, a diverse set of DAC materials will be studied with three main goals: 1) quantify capacity loss due to degradation and identify the mechanisms involved, 2) test accelerated aging protocols with the help of extensive analytical testing to characterize the changes in the DAC materials and 3) carry out long term (>500 cycles) testing and use the results of these tests to validate reliable accelerated aging tests for the material types in the set. Analytical and NETL DAC Center testing will be used to identify failure modes, quantify lifetimes and develop accelerated aging protocols for DAC materials that are national lab developed and/or commercially licensed. These objectives are crucial to the successful commercialization of DAC materials and cannot be achieved without the state-of-the-art laboratory capabilities of the partner national labs and the NETL DAC Center.

Real-time Forecasts of Induced Seismicity with Machine Learning-based Event Detection and Location

Lead lab: Lawrence Livermore National Laboratory

Partner lab: ORNL

Scaling carbon storage technologies to commercial scale necessitates advanced seismic monitoring to efficiently and proactively mitigate potential induced seismicity. Traditional seismic processing techniques often fail in noisy industrial environments, leading to errors and delays in event identification. In collaboration with Instrumental Software Technologies, Inc. (ISTI), LLNL and ORNL, the Real-time inducEd seismiCity forecasts learNiNg sEismic CaTalogs RECONNECT team proposes to develop and couple a real-time machine learning (ML) pipeline (SEMIAI)for improved seismic event detection and location with the Operational Forecasting of Induced Seismicity (ORION) toolkit. This initiative aims to reduce latency time by 20%, classify earthquakes and non-earthquake sources, and provide real-time forecasts of induced seismicity hazards, along with the production of high-precision historic seismic event catalogs. By providing operators with cost-effective, advanced monitoring and forecasting tools, RECONNECT aims to enhance public trust and acceptance while empowering operators to proactively address seismic risks. Real-time monitoring and accurate forecasting will enable swift responses to adverse events, bolstering community safety and public confidence in carbon storage operations.

Optimizing BiCRS and DACS Siting: Dynamic Framework with Feedstock-Driven Process Modeling, Spatial Intelligence, and Smart Co-Location Strategies

Lead lab: Lawrence Livermore National Laboratory

Partner lab: ORNL

The successful deployment of Carbon Dioxide Removal (CDR) technologies relies heavily on selecting the right locations. This project aims to develop a framework for optimizing siting locations of Biomass Carbon Removal and Storage (BiCRS) and DACS facilities based on technology performance, local feedstock variability, local resources and infrastructure, regional economic factors, impacts of CDR facility scale, co-location with other industries, and social legitimacy. The project aims to provide a versatile toolset that CDR technology developers can readily use to evaluate their business concepts and pinpoint optimal locations for deployment of their technologies. Moreover, the toolset can also be used to help communities identify types of CDR projects that will be advantaged by the local characteristics. This toolset will offer a comprehensive perspective, encompassing technical performance, economic viability, environmental impact, and social considerations relevant to the deployment of CDR in specific locations.

Advanced System Analysis Code Assessment and Enhancement to Support the Integral Molten Salt Reactor Design and Licensing

Lead lab: Argonne National Laboratory

The System Analysis Module (SAM) is an advanced and modern system analysis tool for advanced non-light water reactor safety analysis. The goal of this project is to increase the technical maturity of the SAM code for modeling and simulation of Terrestrial Energy’s Integral Molten Salt Reactor (IMSR) design, thus enabling its use in safety analysis of the IMSR design for licensing application. The thrust of the proposed work is to identify and address the gaps in the code’s capability for commercial-grade design and safety analyses of IMSR. Argonne will perform code assessment and enhance SAM modeling capabilities for IMSR systems and components. Argonne will improve the capabilities for modeling noble gas and noble metal fission products behavior in the IMSR, their migration within the primary loop and the pathways for transport across the reactor vessel boundary. Terrestrial Energy USA (TEUSA) will provide guidance in identifying systems, components, phenomena, and processes that must be modeled, as well as proprietary material and design data so that the analysis will be directly applicable to commercial-grade design and safety analyses.

Optimizing Commercial Viability of Advanced Reactors with Thermal Energy Storage by Enhancing FORCE Integrated Energy System Price-Maker Market Modeling

Lead lab: Idaho National Laboratory

Elevating the State of Validation and Uncertainty Quantification in the Bison Fuel Performance Code for Commercialization and Licensing

Lead lab: Idaho National Laboratory

Initial FRI3D Commercial Usage Assistance

Lead lab: Idaho National Laboratory

Optimization of Physical Security Protection through Combined Simulation

Lead lab: Idaho National Laboratory

Autonomous Control for Reactor Technologies

Lead lab: Idaho National Laboratory

Economic assessment of Noble Gas Separation using Metal Organic Frameworks from Nuclear Re-processing Plants

Lead lab: Pacific Northwest National Laboratory

Pacific Northwest National Laboratory (PNNL) in collaboration with CURIO solutions LLC will evaluate the economics of room temperature metal organic framework (MOF)-based adsorption process to compare the energy cost and economic impacts with cryogenic distillation.

Machine Learning Based Intelligent Welding for nuclear reactor component manufacturing and repair

Lead lab: Oak Ridge National Laboratory

This proposal aims at further maturing and commercializing ORNL’s proprietary Artificial Intelligence and Machine Learning based real-time welding monitoring and control approach towards a wide application of the next-generation automated welding and similar wire-arc additive manufacturing processes in a variety of industry sectors including nuclear power industry. The goal is to significantly improve welding manufacturing quality and productivity with reduced cost and production cycles.

MEMS-enabled in operando spectroscopy and imaging during heating

Lead lab: Oak Ridge National Laboratory

This project proposes to develop new in operando scanning/transmission electron microscopy (S/TEM) imaging capabilities with a demonstration on spent nuclear fuel. Integrating microfluidics and nanofluidics into electron microscopy has revolutionized material research. Dr. Yu invented transferrable liquid cells permitting multimodal in situ and in operando imaging including S/TEM and time-of-flight secondary ion mass spectrometry (ToF-SIMS). Micro-Electro-Mechanical Systems (MEMS) offers the advantage of fine localized control of material analysis during in operando heating experiments, while reducing the alpha effect. The new S/TEM compatible cells will have two transparent detection windows to allow electron transmission for analysis. Better fluidic control using microfluidics and nanofluidics instead of O-rings to create flow path is an advancement compared to existing liquid cells. A heating layer consisting of microheater and thermocouples will be used to measure temperature in the detection area and to obtain controlled heating. MEMS design, fabrication, and optimization will be a collaborative effort between ORNL and Norcada. The heating MEMS integration will be performed using the SEM, TEM, and ToF-SIMS instruments at ORNL. Model particles (e.g., SIMFUEL, UO2) will be used to demonstrate radiolytic effects in action and further the lab’s capabilities to study material transformation and corresponding properties under extreme conditions.

TRISO Recycling or Waste Reduction Using SRNL Vapor Digestion Technology

Lead lab: Savannah River National Laboratory

The Savannah River National Laboratory (SRNL) and the University of South Carolina (USC) will work together to advance SRNL intellectual property for the processing and disposal of spent nuclear fuel (SNF) coming from advanced nuclear reactors using high-temperature gas-cooled reactors (HTGRs). Tri-structural isotropic (TRISO) fuel is being used in many advanced reactor designs. However, the HTGR reactors generate 10-16 times more spent fuel discharge volume compared to light-water reactors. An order of magnitude reduction or more in the volume of SNF could be realized if the TRISO particles were separated from the graphite moderator and the carbon dispositioned as low-level waste (LLW). This would substantially reduce the costs associated with storing HTGR SNF. SRNL has a patented vapor digestion process that was developed to disposition spent HTGR fuel at the Department of Energy (DOE) Savannah River Site. Through a mixture of computational fluid dynamics (CFD) modeling, off-gas catalysis experiments, carbon capture studies, and integrated demonstrations, the research team will close the gaps related to the deployment of the SRNL process for handling spent commercial TRISO fuel.

X-ray digital twins (X-twins) for additive manufacturing

Lead lab: Los Alamos National Laboratory

LANL and EWI, a non-profit partner with extensive leadership experience in developing, testing and implementing advanced manufacturing, propose to join effort in maturing X-twin technology to transform automated quality control and certification in additive manufacturing. X-Twin technology is a digital twin technology founded on data fusion principles, novel machine learning accelerated algorithms, existing and pending patents to seamlessly integrate imaging hardware, X-ray data, other sensor data and meta data. The commercialization potential for new quantity control technology to additive manufacturing is similar to cyber security technology to the internet. Two critical pieces of X-Twin will be matured up to TRL 7 and ARL above 7. The potential market share for X-Twin and related technologies could exceed $1B.

Cellulose 2.0 TM, Repurposing Non-recyclable Municipal Solid Waste, through Diversion and Up-cycling Methods

Lead lab: Idaho National Laboratory

Anode-Free Batteries for Commercial Applications

Lead lab: Pacific Northwest National Laboratory

PNNL proposes to demonstrate the scalability and thermal stability of anode free lithium batery (AFLB) technology that has a specific energy density significantly higher than those of Li ion bateries and Li metal bateries. However, current AFLBs still exhibit poor thermal stability, especially in high capacity bateries where safety hazard is a significant challenge. Recently, PNNL has developed a localized high concentration electrolyte (LHCE) that enables AFLBs cycled at high coulombic efficiency and passed nail penetration test in 250 mAh pouch cells, but this is still not big enough for most practical applications. In this project, PNNL will work closely with Aeonix Energy Inc. (a batery company focus on scaling up and commercializing of next-generation bateries such as AFLBs) to scale-up the capacity of AFLB cells to more than 2Ah in their pouch cell production line and demonstrate their thermal stability to enable their practical applications for a broad market. The fundamental understanding obtained during the exploration of AFLBs can also be applied to improve the perfomance of lithium ion and lithium metal bateries, therefore, accelerate market penetration of EVs led by DOE/EERE.

Decarbonizing and improving the profitability of organic waste treatment through an innovative process and value chain

Lead lab: Argonne National Laboratory

Argonne National Laboratory and its partner, Corumat, will develop and demonstrate cost-effective manufacturing technology to produce carbon-negative packaging (CNP) material to decarbonize the packaging industry. Argonne will apply its proprietary separation technology to capture organic acids from an anaerobic digester broth of solid waste with low cost and energy consumption. Once its economic viability is demonstrated, Corumat will deploy the technology along with their patented packaging material manufacture technology to create a circular carbon negative packaging value chain (CCNPVC). Orumat will use the CCNPVC strategy to reduce/or eliminate the solid waste landfill to reduce GHG emissions and also create job trainings and job opportunities in disadvantaged communities.

Integrated processing and hydrothermal pretreatment of corn stover into a second-generation ethanol facility

Lead lab: Idaho National Laboratory

Partner lab: NREL

Economical, Effective Ductless Heat Pumps for Cold Climates

Lead lab: National Renewable Energy Laboratory

Cold climates face building decarbonization challenges, with many buildings relying on fossil fuels for heating. Heat pumps currently on the market can operate effectively down to temperatures well below 0°F but installation requires skilled trades that can be lacking, especially in rural areas. NREL researchers developed an easy-to-install ductless mini-split heat pump (DHP) connection technology, EcoSnap, which removes the need for handling refrigerant, fabricating refrigerant connections, or wiring the unit directly to the panel as is required for traditional DHP installation. EcoSnap-enabled heat pumps eliminate the need for skilled labor and reduce the installation time by hours, decreasing labor costs. This project supports commercialization of the EcoSnap joining technology for easy and lower cost installation of DHPs by validating the reliability of the connection system and performing field demonstrations in two different cold climates, proving real-world performance. The project goal is advanced commercialization of the EcoSnap technology to an ARL and TRL of 8 to provide a lower-cost heat pump installation option in all climates. It benefits rural locations with a lack of skilled labor, urban locations where contractors are trying to decrease installation time and cost, and homeowners who are burdened with high fuel costs.

Enabling the Commercialization of Advanced Facade Controls

Lead lab: Lawrence Berkeley National Laboratory

This project advances LBNL’s automated façade controls tools towards commercialization and industry adoption through 1) integration with commercially-available equipment in the context of an industry-led field demonstration of automated shading; 2) improving LBNL tools, based on industry partner feedback, in order to enhance usefulness in deployment applications; 3) and documentation and dissemination of project results to relevant stakeholders, including building owners/operators, installation/commissioning entities, organizations in disadvantaged communities, workforce training organizations, labor, designers, manufacturers, and utilities.

Commercialization of High Temperature Downhole Generator for Geothermal Drilling Applications

Lead lab: National Renewable Energy Laboratory

Novel high energy drilling methods have the potential to greatly increase drilling rate of penetration in hard, hot, geothermal rock types while reducing delays due to required maintenance and downtime. However, these drilling systems require large amounts of electricity downhole, and running an electric cable downhole for supplying power has several challenges that make it economically and technically infeasible. The National Renewable Energy Laboratory (NREL) has designed and demonstrated a novel generator, with exceptional performance, for downhole power generation during geothermal drilling. This technology allows for electricity generation at the bottom of the well without the need to run power cables down the drill string. The generator is designed for the harsh, corrosive environment at the bottom of a geothermal well, and to operate at ambient temperatures of 250°C. To commercialize this technology, NREL is partnering with GA Drilling, a geothermal drilling company who specializes in novel drilling methods. NREL and GA Drilling will further develop this generator technology by integrating it into their PLASMABIT Hybrid drilling solution. The aim of this project is to advance this technology to the point where it is ready for field testing in a full-scale commercial drilling system.

Scale-Up of High-Performance Proton Conducting Solid Oxide Electrolysis Cells (p-SOECs) and Development of the Short-Stack for Low-cost Hydrogen Production at Intermediate Temperatures

Lead lab: Idaho National Laboratory

High Filler, Low Water (HFLW) Concrete: Predictive Design and Production Protocol in Ready-Mix Application

Lead lab: Oak Ridge National Laboratory

This project proposes to develop tools to accelerate deployment of HFLW concrete in the U.S. that include (i) a predictive HFLW concrete design software for optimized mechanical performance, durability, and service life, and (ii) concrete mixing and slump management protocols using existing in-transit management tools to enable HFLW concrete production in ready-mix trucks. The development of these tools will accelerate adoption of HFLW enabling reduction U.S. concrete industry’s CO2 emissions by nearly half in the near term if broadly adopted because it is a nearly drop-in replacement to conventional concrete. In HFLW concrete, the contents of cement and water can be reduced by as much as 75% and 50%, respectively, compared to conventionally designed concrete. Fine fillers are added to fill the voids of concrete’s granular skeleton, and chemical dispersants are added at saturation level. HFLW leverages existing supply chain and industrial infrastructure. ORNL has recently demonstrated technical and economic feasibility with up to ~50% CO2 reduction compared to conventional concrete, low investment, and low operational costs in precast/prestressed concrete application. The development of the proposed tools will remove barriers to rollout the technology to the ready-mix market that supplies 70% of the concrete produced in this country.

rGO-Enhanced Nanocomposite Electromembrane Technology for Energy Efficient Water Desalination

Lead lab: Argonne National Laboratory

Argonne National Laboratory and GOLeafe collaborate to develop a novel rGO-enhanced hydrocarbon-based electromembrane that enables low-cost, energy-efficient brackish water desalination and industry wastewater valorization. When integrated with recirculated electrodialysis (ED) processes and high-efficiency solar/wind evaporation such as interfacial photothermal evaporation, this technology can facilitate zero liquid discharge (ZLD) due to its electric field driven high separation efficiency.

Rapid High Temperature Carbonization (HTC) Through Metal Bath

Lead lab: Oak Ridge National Laboratory

A new high temperature carbonization technology for the manufacturing of carbon fiber (CF) will be developed that is projected to reduce the energy consumption of this stage by at least 40% while increasing throughput up to 6X. At the end of the project, the pilot line will be able to process 4x50k CF tows with properties acceptable to the car industry with a unit energy consumption of 2 kWh/lb. or less. This novel method relies on the use of a liquid to transfer heat and carbonize the material. Whereas the conventional processes usually rely on very high temperature heating by pure radiation, this novel method presented here aims to process the material through direct contact heat transfer to the fiber. In this method, the material is immersed into a liquid metal set at the desired process temperature. Residence time reduction is substantial, hence contributing significant energy savings and decarbonization of the HTC process. Initial experimental work has already been completed with the results shared herein. The project team has a clear path to rapid commercialization with a high growth industrial partner on board.

Energy-Transit Nexus Tools for Bus Fleet Electrification (NEXTBUS)

Lead lab: National Renewable Energy Laboratory

Transit agencies are uniquely positioned as high visibility early adopters of medium- and heavy-duty battery electric vehicles. This brings with it significant opportunities and challenges during this transition. Transit agencies have highlighted the complications that electrification adds to day-to-day operations as a critical barrier that must be addressed. This project aims to address this need through commercialization of NREL technology in ReVolt’s software platform to optimize battery electric transit bus fleets through detailed crew rostering, bus scheduling, and charge planning. NREL vehicle energy modeling and complex fleet optimization through tools such as FASTSim, RouteE, and ASPIRES are well-suited to this problem space. These opensource tools in a more accessible and usable form will allow transit agencies and fleet operators to schedule and operate their electric bus fleet most efficiently given their existing infrastructure options. ReVolt Battery Technology is developing commercial products to solve many of the planning, scheduling, and operations challenges that transit agencies face as they electrify their fleets. Together, NREL and ReVolt intend to commercialize NREL’s energy modeling and optimization technology through ReVolt’s software products to realize significant energy and emissions reductions in public transportation.

Advancing Detailed Jet Engine Simulation with Small, Accurate Kinetic Models and GPU Solvers

Lead lab: Lawrence Livermore National Laboratory

This project will push gas-turbine design forward, accelerating the design cycle for the creation of new reliable, efficient, and clean jet engines and reducing the climate impact of aviation. Lawrence Livermore National Laboratory will collaborate with GE Aerospace to reduce the computational cost of predictive gas-turbine combustor simulations through the generation of small, accurate chemical reaction models and efficient graphical processing unit (GPU) chemistry solvers. The goal of the project is to reduce the time-to-solution for industry relevant simulations by greater than 50%. The ability to drive down the model size and computational cost while maintaining accuracy will be a key enabler for GE Aerospace and others in the jet-turbine industry to design next-generation combustors and help the U.S. meet future sustainability and emissions goals.

Industry-Requested Wind Turbine Model Validation Method Using National Laboratory Measurement Expertise

Lead lab: Sandia National Laboratories

Wind turbine original equipment manufacturers (OEMs) rely on aeroelastic models of their turbines to design new products with both high performance and reliability. Recent fleetwide failures of turbine reliability at several large OEMs have exposed flaws in the modeling process and the corresponding model validation process. According to industry contacts, the most fundamental shortcoming in model validation based on measurements from a prototype installation is the inflow, which is typically recreated in simulations using pseudo-physical models that cannot match exactly what a prototype experiences. Recent efforts at Sandia National Laboratories (SNL) have resulted in development of a unique measurement capability that could work in service of the OEM model validation process. Specifically, SNL has developed expertise in a hub-mounted Doppler-lidar technology that could fundamentally alter the landscape of the industry model validation process by providing a never-before-used level of spatial and temporal resolution to characterize the inflows to their prototypes. The technology was recently demonstrated in a limited way in a DOE-funded effort between SNL, NREL, and GE Vernova. This project will work to advance the state-of-the-art to the level necessary for OEM adoption at a production level.

Toward Commercialization of Hydrophone Flow Shields to Improve Acoustic Data Quality

Lead lab: Pacific Northwest National Laboratory

This project aims to perform testing, market research, and manufacturing refinement to ready patent-pending hydrophone flow shields developed at PNNL for commercialization. The flow shields significantly reduce the impact of flow noise on underwater noise recordings in areas of strong flow (e.g., tidal channels). Flow noise is a challenge for many applications of underwater passive acoustic monitoring, including measuring the sound produced by marine energy converters and monitoring marine mammals. This project will answer several key questions about flow shield performance that are high-priority for potential customers and refine existing manufacturing processes so that they are scalable for market-level production. If successful, commercialization of flow shields will facilitate high-quality, cost-effective environmental monitoring of marine renewable energy converters.

• An Acoustic Transmitter with Intelligent ON/OFF Mechanisms and Quasi-location Awareness
• Lead lab: Pacific Northwest National Laboratory

Acoustic telemetry has been one of the primary methods for understanding the environmental impact of hydropower systems. Several small acoustic transmitters and sensor devices recently developed by PNNL, including the eel/lamprey transmitter and Lab-on-a-Fish, have significantly enhanced the capability to study the survival and migration behavior of fish. However, as with any autonomous electronic device, especially micro devices, the finite energy capacity of their batteries is the key bottleneck. These devices generally only last for several months, even though their batteries account for about half of their weight and volume. On the other hand, for many fish tracking applications, it is not necessary to have the acoustic transmitters continuously pinging. Therefore, conserving the limited-service life of an acoustic transmitter would be possible if it were aware of its current location or environment and could intelligently manage its own operation. This project proposes to optimize and commercialize an acoustic transmitter prototype with intelligent ON/OFF mechanisms and quasi-location awareness. The prototype has (1) the ability to turn the transmitter on and off when it passes through a passive integrated transponder antenna (radio frequency-enabled ON/OFF) and (2) the ability to detect significant salinity changes and turn itself on and off accordingly.

Improving marine energy production through commercialization of a low-cost, drag-reducing slippery coating

Lead lab: Pacific Northwest National Laboratory

Marine energy capture systems offer great promise for providing clean energy, but they operate in a challenging and dynamic environment and must be optimized to the highest extent possible. Computational studies predict that drag reduction on marine energy and blue economy systems will result in meaningful improvements in energy efficiency. Based on extensive coating experience, PNNL is proposing to bring to market a new drag-reducing coating called Superhydrophobic Lubricant-Infused Drag-Efficient Coating – SLIDE-Coat. PNNL has a deep knowledge base regarding this class of slippery coatings, and they have a group of enthusiastic industry partners who have committed to partnering, conducting field testing, and providing cost share. In addition to validating the technology, the team will create a commercialization roadmap to ensure the commercial success of the technology after the project's two-year period of performance is complete.

Mobilizing Under-utilized Vessels for Tidal Energy Capture

Lead lab: Sandia National Laboratories

Many coastal communities in Alaska have untapped tidal or river energy and in the offseason, many vessels that sit idle especially during the late fall and winter. This corresponds to a period of high electrical demand (e.g., home heating) and, for communities powered by traditional hydropower, low electrical power availability. During these times, these vessels can be used as floating energy making platforms by installing temporary, deployable tidal or river current energy capturing systems. This work aims to provide vessel owners and remote coastal/river communities a potential source of supplemental income while also supplying predictable, renewable energy during this period of high demand. Through partnerships with Sitkana and Hydrodynamic Power Systems, respectively, this research aims kickstart the adoption existing deployable tidal energy capture systems capable of recharging vessel batteries (near-term) while also supplementing larger, grid-connected arrays. Sandia National Laboratories will assist with the design, operation, and testing of these systems. To facilitate the adoption of such tidal energy capture systems, Sandia will create/update a freely available, open-source software tool that can provide the user and communities at large with recommendations for cost-effective energy capture system parameters for a given current energy resource and vessel pairing.

Enabling the Ocean of Things through a Sustainable Kelp-Inspired Marine Energy Conversion Technology

Lead lab: National Renewable Energy Laboratory

Ocean data is the foundation for improved understanding, use, and protection of our vital marine resources and blue economies, and yet it is severely limited by available power at sea. By harnessing marine energy to continuously power real-time data solutions, NREL's pkelp technology can unlock the Ocean of Things and maximize the impact of DOE funding on marine monitoring, ocean observation, climate/ocean science, and more. This project will drastically accelerate the development and deployment of NREL's pkelp technology, thus enabling greater impact in much less time.