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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

High-Capacity Aqueous Storage in Vanadate Cathodes Promoted by the Zn-Ion and Proton Intercalation and Conversion–Intercalation of Vanadyl Ions

Aqueous Zn-ion batteries (AZIBs) are promising alternatives to lithium-ion batteries in stationary storage. However, limited storage capacity and cyclic life impede their large-scale implementation. In this study, we report reversible electrochemical insertion of multi-ions into sodium vanadate (NaV 3 O 8 ) cathode materials for AZIBs, achieving a maximum storage capacity of 450 mAh g –1 at 0.05 A g –1 and a capacity retention of 82% after 500 cycles at 0.4 A g –1 . In addition to Zn 2+ and H + insertion, in situ X-ray diffraction (XRD) and X-ray absorption spectroscopy (XAS) collectively provide explicit evidence on vanadyl ions (VO 2+ ) conversion–intercalation at the NaV 3 O 8 cathode, showing the deintercalation of VO 2+ from NaV 3 O 8 and the consequent conversion of VO 2+ into V 2 O 5 on charging, and vice versa on discharging. Our study is the first to report on the cation conversion–intercalation mechanism in AZIBs. This reversible multi-ion storage mechanism provides a design principle for developing high-capacity aqueous electrode materials by engaging both the intercalation and conversion of charge carriers.

25 ENERGY STORAGE↗
DOE OSTI2022

Heteroatom-Doped Graphenes as Actively Interacting 2D Encapsulation Media for Mg-Based Hydrogen Storage

Nanoencapsulation using graphene derivatives enables the facile fabrication of two-dimensional (2D) nanocomposites with unique microstructures and has been generally applied to many fields of energy materials. Particularly, metal hydrides such as MgH 2 encapsulated by graphene derivatives have emerged as a promising hybrid material for overcoming the disadvantageous properties of Mg-based hydrogen storage. Although the behavior of the graphene–Mg nanoencapsulation interface has been studied for many composite materials, the direct modification of graphene with nonmetal foreign elements for changing the interfacial behavior has been limitedly reported. In this regard, using B-doped graphene and N-doped graphene as nanoencapsulation media for tuning the interfacial behavior of graphene derivative–Mg nanoparticles, we present altered hydrogen storage kinetics of heteroatom-doped (B and N) graphene–Mg composites. The effect of heteroatom doping is studied in terms of bonding configurations and heteroatom doping concentrations. The enhancement in hydrogen uptake was observed for all of the heteroatom-doped graphene–Mg nanocomposites. On the other hand, a few samples exhibit significantly low activation energy at the early stage of desorption, which can be related to the facilitated nucleus formation. Density functional theory calculation indicates that B-doping and N-doping accelerate hydrogen absorption kinetics in different ways, aiding charge transfer and inducing surface deformation of Mg nanoparticles, respectively. Their effects can be augmented in the presence of structural defects on graphene, such as vacancies, pores, or graphene edges. These results demonstrate that hydrogen storage kinetics of Mg-based systems can be altered by utilizing heteroatom-doped graphene oxide derivatives as 2D nanoencapsulation media, suggesting that the addition of a nonmetal doping element can also be applied to Mg-based hydrogen storage by modifying the nanoencapsulation interface without forming Mg alloy phases.

08 HYDROGEN↗
DOE OSTI2026

Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling as Catalysts for Next-Generation Breakthroughs

The Presidential Symposium (PRES) at the 2025 Fall Meeting, hosted by the President’s Office and Energy and Fuels Division, American Chemical Society (ACS) in Washington, DC, brought together a diverse group of chemists, engineers, and materials scientists working in battery materials & systems, automation and artificial intelligence from academia, industry, and national laboratories. The accelerating demand for high-performance, scalable, and sustainable energy storage has catalyzed a paradigm shift in how materials are dis-covered, devices are engineered, and systems are optimized. This Presidential Symposium, entitled “Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling Driving Next-Gen Breakthroughs”, brings together global leaders to unveil transformative strategies anchored in the AAA framework: Artificial Intelligence, Automation, and Advanced Modeling. Artificial Intelligence is redefining the frontiers of energy storage by enabling predictive design, real-time optimization, and intelligent control across diverse chemistries and architectures. Automation is streamlining the synthesis, characterization, and testing of battery materials, dramatically accelerating innovation cycles and unlocking scalable solutions for grid and mobility applications. Advanced Modeling, spanning atomic to system-level scales, provides unprecedented insight into electrochemical dynamics, degradation pathways, and thermal behavior, particularly when coupled with physics-informed machine learning and digital twin technologies. Digital twins, in turn, leverage the AAA framework by integrating real-time data, physics-based models, and AI predictions into dynamic virtual replicas, enabling proactive diagnostics, optimization, and system resilience. Together, these synergistic pillars are not only re-shaping the scientific landscape but also forging a new era of reproducible, data-driven, and resilient energy storage innovation. In conclusion, this symposium marks a pivotal moment in the convergence of computational intelligence and experimental rigor, charting the course for next-generation breakthroughs in lithium-ion, solid-state, and flow battery technologies.

Artificial Intelligence (AI)↗
DOE OSTI2020

Effect of Thermal Storage on the Emissions and Efficiency Performance of a Wood Pellet-Fired Residential Boiler

Wood pellet boilers for residential heating applications offer the promise of low emissions, high efficiency, and automatic operation. However, when operated in the field, these units operate often at very low loads causing them to cycle. In this study, the performance of a 25-kW modern pellet boiler under emulated field conditions and fixed nominal loads of 15% and 100% has been studied in a lab—with and without a buffer tank. A dilution tunnel approach was used for the measurement of particulate emissions, in accordance with U.S. certification testing requirements under EPA Methods 28 WHH and 28 WHH PTS. Results show that increasing the amount of thermal storage used decreases cycling rates leading to decreased emissions and increased efficiency. Without thermal storage, integrated efficiency over a 15% load test period was 57%, compared to 74% when thermal storage was used. Particulate emissions were 180 mg/MJ and 64 mg/MJ for the 15% load case without and with thermal storage, respectively.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Interlayer gap widened $α$-phase molybdenum trioxide as high-rate anodes for dual-ion-intercalation energy storage devices

Employing high-rate ion-intercalation electrodes represents a feasible way to mitigate the inherent trade-off between energy density and power density for electrochemical energy storage devices, but efficient approaches to boost the charge-storage kinetics of electrodes are still needed. Here, we demonstrate a water-incorporation strategy to expand the interlayer gap of α-MoO 3 , in which water molecules take the place of lattice oxygen of α-MoO 3 . Accordingly, the modified α-MoO 3 electrode exhibits theoretical-value-close specific capacity (963 C g –1 at 0.1 mV s –1 ), greatly improved rate capability (from 4.4% to 40.2% at 100 mV s –1 ) and boosted cycling stability (from 21 to 71% over 600 cycles). A fast-kinetics dual-ion-intercalation energy storage device is further assembled by combining the modified α-MoO 3 anode with an anion-intercalation graphite cathode, operating well over a wide discharge rate range. Our study sheds light on a promising design strategy of layered materials for high-kinetics charge storage.

25 ENERGY STORAGE↗
DOE OSTI2021

Atomic/molecular layer deposition for energy storage and conversion

Energy storage and conversion systems, including batteries, supercapacitors, fuel cells, solar cells, and photoelectrochemical water splitting, have played vital roles in the reduction of fossil fuel usage, addressing environmental issues and the development of electric vehicles. The fabrication and surface/interface engineering of electrode materials with refined structures are indispensable for achieving optimal performances for the different energy-related devices. Atomic layer deposition (ALD) and molecular layer deposition (MLD) techniques, the gas-phase thin film deposition processes with self-limiting and saturated surface reactions, have emerged as powerful techniques for surface and interface engineering in energy-related devices due to their exceptional capability of precise thickness control, excellent uniformity and conformity, tunable composition and relatively low deposition temperature. In the past few decades, ALD and MLD have been intensively studied for energy storage and conversion applications with remarkable progress. In this work, we give a comprehensive summary of the development and achievements of ALD and MLD and their applications for energy storage and conversion, including batteries, supercapacitors, fuel cells, solar cells, and photoelectrochemical water splitting. Moreover, the fundamental understanding of the mechanisms involved in different devices will be deeply reviewed. Furthermore, the large-scale potential of ALD and MLD techniques is discussed and predicted. Finally, we will provide insightful perspectives on future directions for new material design by ALD and MLD and untapped opportunities in energy storage and conversion.

25 ENERGY STORAGE↗
DOE OSTI2023

Advancing energy storage through solubility prediction: leveraging the potential of deep learning

Solubility prediction plays a crucial role in energy storage applications, such as redox flow batteries, because it directly affects the efficiency and reliability. Researchers have developed various methods that utilize quantum calculations and descriptors to predict the aqueous solubilities of organic molecules. Notably, machine learning models based on descriptors have shown promise for solubility prediction. As deep learning tools, graph neural networks (GNNs) have emerged to capture complex structure–property relationships for material property prediction. Specifically, MolGAT, a type of GNN model, was designed to incorporate n-dimensional edge attributes, enabling the modeling of intricacies in molecular graphs and enhancing the prediction capabilities. In a previous study, MolGAT successfully screened 23 467 promising redox-active molecules from a database of over 500 000 compounds, based on redox potential predictions. This study focused on applying the MolGAT model to predict the aqueous solubility (log S) of a broad range of organic compounds, including those previously screened for redox activity. The model was trained on a diverse sample of 8494 organic molecules from AqSolDB and benchmarked against literature data, demonstrating superior accuracy compared with other state of the art graph-based and descriptor-based models. Subsequently, the trained MolGAT model was employed to screen redox-active organic compounds identified in the first phase of high-throughput virtual screening, targeting favorable solubility in energy storage applications. The second round of screening, which considered solubility, yielded 12 332 promising redox-active and soluble organic molecules suitable for use in aqueous redox flow batteries. Thus, the two-phase high-throughput virtual screening approach utilizing MolGAT, specifically trained for redox potential and solubility, is an effective strategy for selecting suitable intrinsically soluble redox-active molecules from extensive databases, potentially advancing energy storage through reliable material development. This indicates that the model is reliable for predicting the solubility of various molecules and provides valuable insights for energy storage, pharmaceutical, environmental, and chemical applications.

25 ENERGY STORAGE↗
DOE OSTI2023

Hydrogen storage in liquid hydrogen carriers: recent activities and new trends

Abstract Efficient storage of hydrogen is one of the biggest challenges towards a potential hydrogen economy. Hydrogen storage in liquid carriers is an attractive alternative to compression or liquefaction at low temperatures. Liquid carriers can be stored cost-effectively and transportation and distribution can be integrated into existing infrastructures. The development of efficient liquid carriers is part of the work of the International Energy Agency Task 40: Hydrogen-Based Energy Storage. Here, we report the state-of-the-art for ammonia and closed CO 2 -cycle methanol-based storage options as well for liquid organic hydrogen carriers.

08 HYDROGEN↗
DOE OSTI2026

Light storage, retrieval, and controllable interference in an atomic tripod system

Highly efficient quantum memories are essential for advancing quantum information processing technologies, including scalable quantum computing and quantum networks. We experimentally demonstrate a light storage and retrieval protocol in a tripod system using an ensemble of laser-cooled 87 Rb atoms. The tripod system, which consists of three ground states and an excited state, offers rich dynamics: its use to coherently store and retrieve a weak probe pulse in the 87 Rb 𝐹 = 1 ground-state manifold leads to the interference of two spin-wave excitations during storage time that translate to an interference in the peak intensity of the retrieved probe pulse. Our work shows that these interferences, which manifest when varying the pulse sequence or energy level structure, can be controlled experimentally by varying the storage time, optical phase, and magnetic field strength. Theoretical simulations exhibit excellent agreement with the experimental results. In conclusion, this work demonstrates the rich dynamics and versatile capabilities of atomic tripod systems for light storage and retrieval, with key advantages over conventional Λ systems, highlighting the potential of atomic tripod systems for applications in quantum information processing, quantum synchronization, and atomic memory protocols.

Coherent control↗
DOE OSTI2021

MOSIQS: Persistent Memory Object Storage With Metadata Indexing and Querying for Scientific Computing

Scientific applications often require high-bandwidth shared storage to perform joint simulations and collaborative data analytics. Shared memory pools provide a chance to satisfy such needs. Recently, a high-speed network such as Gen-Z utilizing persistent memory (PM) offers an opportunity to create a shared memory pool connected to compute nodes. However, there are several challenges to use scientific applications on the shared memory pool directly such as scalability, failure-atomicity, and lack of scientific metadata-based search and query. In this paper, we propose MOSIQS, a persistent memory object storage framework with metadata indexing and querying for scientific computing. We design MOSIQS based on the key idea that memory objects on PM pool can live beyond the application lifetime and can become the sharing currency for applications and scientists. MOSIQS provides an aggregate memory pool atop an array of persistent memory devices to store and access memory objects to accelerate scientific computing. MOSIQS uses a lightweight persistent memory key-value store to manage the metadata of memory objects, which enables memory object sharing. To facilitate metadata search and query over millions of memory objects resident on memory pool, we introduce Group Split and Merge (GSM), a novel persistent index data structure designed primarily for scientific datasets. GSM splits and merges dynamically to minimize the query search space and maintains low query processing time while overcoming the index storage overhead. MOSIQS is implemented on top of PMDK. We evaluate the proposed approach on many-core server with an array of real PM devices. Experimental results show that MOSIQS gains a 100% write performance improvement and executes multi-attribute queries efficiently with 2.7× less index storage overhead offering significant potential to speed up scientific computing applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Virtual Log-Structured Storage for High-Performance Streaming

Over the past decade, given the higher number of data sources (e.g., Cloud applications, Internet of things) and critical business demands, Big Data transitioned from batch-oriented to real-time analytics. Stream storage systems, such as Apache Kafka, are well known for their increasing role in real-time Big Data analytics. For scalable stream data ingestion and processing, they logically split a data stream topic into multiple partitions. Stream storage systems keep multiple data stream copies to protect against data loss while implementing a stream partition as a replicated log. This architectural choice enables simplified development while trading cluster size with performance and the number of streams optimally managed. This paper introduces a shared virtual log-structured storage approach for improving the cluster throughput when multiple producers and consumers write and consume in parallel data streams. Stream partitions are associated with shared replicated virtual logs transparently to the user, effectively separating the implementation of stream partitioning (and data ordering) from data replication (and durability). We implement the virtual log technique in the KerA stream storage system. When comparing with Apache Kafka, KerA improves the cluster ingestion throughput by up to 4x when multiple producers write over hundreds of data streams.

consistent stream ordering↗
DOE OSTI2020

A 150-kW 99% Efficient All-Silicon-Carbide Triple-Active-Bridge Converter for Solar-Plus-Storage Systems

Solar-plus-storage systems could effectively mitigate the uncertainties of the photovoltaic (PV) generation and improve system reliability by adding an integrated battery energy storage system. As a three-port bidirectional isolated dc–dc converter with soft-switching capability, the triple-active-bridge (TAB) converter inherently matches the requirements of the solar-plus-storage system. However, challenges still remain in the TAB converter design to further improve system efficiency. In this article, the detailed design, implementation, and demonstration for a silicon carbide (SiC) 150-kW TAB converter are presented. Starting from a brief review of the TAB converter, the modulation scheme, power characteristics, and soft-switching region are analyzed. Then, the detailed design of the H-bridge converter building block is given. Here, to improve the system efficiency, a comprehensive characterization of the SiC gate driver with various external gate resistances is performed to address tradeoffs between switching loss and voltage overshoot during transients, as well as the thermal performance of the H-bridge building block. In addition, the design and characterization of the 20-kHz three-port transformer are also given. Comprehensive experimental studies are conducted on a full-power prototype to verify the proposed design. With a measured 99.1% peak efficiency, the proposed TAB converter can fulfill the requirements for solar-plus-storage applications.

14 SOLAR ENERGY↗
DOE OSTI2023

Exploring the Storage Mechanism of Alkali Ions in Non-Graphitic Hard Carbon Anodes

This study aims to develop high-capacity hard carbon anode materials for alkali-ion batteries by controlling the microstructures of non-graphitic hard carbon through an annealing protocol and investigating the effects on the alkali-ion storage mechanisms using physical, chemical, and electrochemical analytical techniques. The hard carbon materials were synthesized at temperatures ranging from 900 °C to 1600 °C. Those synthesized at 1100 °C with high surface area and abundant defects exhibited the highest reversible capacity in Li- and K-ion systems, with the storage dominated by surface-adsorption mechanisms. In contrast, the hard carbon compounds prepared at 1400 °C with numerous curve-featured pores delivered the highest reversible capacity in the Na-ion system, indicating that these pores are the preferred Na-ion storage sites, particularly in low-voltage plateau regions. This study provides a comprehensive understanding of the relationship between microstructures and alkali-ion storage mechanisms in non-graphitic hard carbon and highlights the importance of tailoring the microstructures of hard carbon to achieve high specific capacity for the desired alkali-ion species.

25 ENERGY STORAGE↗
DOE OSTI2022

Intermountain West Energy Sustainability & Transitions Initiative: CO2 Transport and Geologic Storage Modeling Results

These resources provide the full set of cost modeling results and methods as part of the I-WEST Roadmap Initiative that were used to compile figures as part of the "Pathways to CO2 Utilization and Storage for the Intermountain West Region" chapter. The data were generated from a series of National Energy Technology Laboratory (NETL) cost models and relate to carbon dioxide (CO2) transport costs, CO2 enhanced oil recovery (CO2-EOR) economics, and saline storage economics. These models were used to analyze various business cases given changes in technical and financial assumptions for the I-WEST region as a means to explore how these assumptions influence CO2 transport and storage costs, as well as to evaluate the effect of changing oil prices on the viability of CO2-EOR and the mass of CO2 stored via CO2-EOR. The accompanying report titled "Intermountain West Energy Sustainability & Transitions Initiative: CO2 Transport and Geologic Storage Modeling Results" provides a detailed overview on the models, assumptions, and parameters used in the modeling, as well as example results..

CO2 EOR costs,CO2 Storage Costs,CO2 transportation↗
DOE OSTI2020

Evaluation of Containment and Geomechanical Risks at Integrated Mid-Content Stacked Carbon Storage Hub Sites

The U.S. Department of Energy is leading the development of CCS through collaborative projects and programs to not only develop and demonstrate the technology but to also quantify the risks and provide tools that site operators can use to develop a site-specific understanding of their risk to enable successful project operations. This report summarizes results and findings from the application of risk-assessment tools to an industrial-scale Geologic Carbon Storage (GCS) project. Specifically, we applied the National Risk Assessment Partnership’s (NRAP) Open Integrated Assessment Model (NRAP-Open-IAM) and State of Stress Assessment Tool (SOSAT) to two candidate sites being considered for storage by the Integrated Midcontinent Stacked Carbon Storage Hub (IMSCS-Hub) project team. These sites, Sleepy Hollow Field in Nebraska and Patterson Field in Kansas, have historical oil and gas production and thus are attractive candidates to store the 50 million metric tons (Mt), which is the CarbonSAFE objective. Because these sites have historical operations, they have a significant number of existing wells that pose a risk for well leakage. Additionally, the storage formations will undergo significant pore pressure perturbation (i.e., increase due to CO 2 injection). Hence, we have selected the two NRAP tools best suited to study the risks associated with well leakage and geomechanical risks. The objective of the study was not only to assess the risk at the site, but to also improve the NRAP tools through application using real site data on an ongoing project.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Regional Assessment for the CO 2 Storage Potential in the Northern Niagaran Pinnacle Reef Trend

The Midwest Regional Carbon Sequestration Partnership (MRCSP) was founded in 2003 as part of the U.S. Department of Energy’s (DOE’s) Regional Carbon Sequestration Partnership initiative. Since its founding, MRCSP has made significant strides toward making CCUS a viable option for states in the region. The public/private consortium, funded through the DOE Regional Carbon Sequestration Initiative, brings together nearly 40 industry partners and 10 states. Battelle, as the project lead, oversees research, development and operations and coordinates activities among the partners. The incremental, phased approach has built a valuable knowledge base for the industry and paved the way for commercial-scale adoption of CCUS technologies. From 2008 to 2020, MRCSP Phase III focused on the development of large-scale injection projects. This report is part of a series of reports prepared under the Midwestern Regional Carbon Sequestration Partnership (MRCSP) Phase III (Development Phase). These reports summarize and detail the findings of the work conducted under the Phase III project. The report describes the regional analysis of the Northern Niagaran Pinnacle Reef Trend (NNPRT) in Northern Michigan as part of the MRCSP programs Regional Assessment goals. The goal of this task was to perform an initial assessment of the geologic storage capacity and injectivity of the Northern Fairway of Michigan’s Niagaran Reef Trend. This was achieved through three main objectives: 1) development of a reef atlas, 2) understanding the regional trends in geology, and 3) estimating CO 2 and CO 2 -EOR resources. Data collected across multiple subtasks were integrated into a mappable database that could be accessed from many of the leading software. The reef atlas was used to map the reefs and associated characteristics across the entire NNPRT. Several methodologies were explored to estimate the CO 2 and CO 2 -EOR resources across the trend which included three scenarios: 1) storage only using fluid substitution and volumetric estimations, 2) CO 2 -EOR which applied proximity analysis concepts and measured performance metrics from the Core Energy reefs to predict performance at all oil reefs, and 3) enhanced storage scenario which combined CO 2 -EOR with fluid substitution to represent maximized storage after completion of CO 2 -EOR.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

A Rechargeable Carbon-Oxygen Battery for Efficient, Low-Cost Energy Storage

As part of the Cyclotron Road program, Noon Energy Inc investigated the feasibility of a new class of rechargeable flow battery for long-duration energy storage at the 100+ hour storage capacities needed to make intermittent solar/wind power available 24/7 year-round. Whereas conventional batteries store energy in relatively expensive metals like cobalt, lithium, and vanadium, the new battery stores energy in abundant, ultra-low-cost carbon and oxygen, storage media that cost well below $1 per kWh capacity (less than the cost of their containers). It also can operate with a high roundtrip energy efficiency of ~80% and has 10x higher energy density than conventional aqueous flow batteries, even higher than lithium ion batteries at system level. These properties make it suitable for a variety of potential stationary energy storage applications as well as for electric transportation vehicles (long-haul marine shipping and trucking), so determining the best product-market fit and market entry was a key outcome of Noon’s Cyclotron Road fellowship. Noon had demonstrated initial materials development and proof-of-principle testing before the fellowship. Overall, within the fellowship Noon carried out key initial technology development in market applications, system design, risk assessment and prototyping.

25 ENERGY STORAGE↗
DOE OSTI2021

Collaboration to Enable Higher Penetrations of Solar Power Generation Using the Natural Gas Pipeline System for Energy Storage (CRADA CRD-14-00567)

This unique project explored one possible solution for photovoltaic (PV) generation to become a reliable and dispatchable energy resource similar to conventional baseload fossil fuel electricity generation. Solar power generation is a renewable resource that varies naturally from day-to-day as well as seasonally. To use solar power as a baseload generation asset requires a flexible storage system that can recover power on both a daily and seasonal basis. Converting solar power to natural gas (i.e., first to hydrogen and then to methane) and having access to utility-scale storage in the natural gas network has the potential to make solar power generation a baseload asset. This will: 1) Increase the net energy yield from solar resources by increasing the effective capacity factor and maximize the energy produced during the assets’ lifetimes. 2) Improve the economics of energy storage for solar project developers, thereby accelerating the deployment of new solar generation. 3) Reduce the impact of increasing solar penetration on congestion of the electrical transmission system by shifting power delivery in time using the gas pipeline network for long-duration storage. 4) Reduce the impact of increasing solar generation on electrical distribution system control. 5) Offer alternative revenue sources for solar power generation beyond electricity including: hydrogen (H 2 ) production for stationary fuel cells and fuel cell electric vehicles, conversion of carbon dioxide (CO 2 ) to methane (CH 4 ) as a direct drop-in replacement for fossil natural gas use, and transmission as high volumetrically-dense CH 4 for use in transportation, heating, power generation, chemical production or conversion back to H2 at the point of use. Additional work was added to this CRADA in modification 4 having a primary objective to characterize the performance of the electrolyzer, Southern California Gas (SoCalGas) bioreactor and balance of plant to demonstrate production of renewable natural gas (RNG) from renewable H 2 and CO 2 using single-cell, self-replicating organisms. The additional scope of work allowed researchers to ramp up gas flowrates and pressure of the system over the designed range to grow the cells and begin to show the load-following capabilities of this anaerobic gas fermentation process. These activities enabled the research team to predict system performance at much greater scales; namely 10’s of mega-watts (MWs) of electrolyzer nameplate capacity.

14 SOLAR ENERGY↗