SEARCH · Search NASA

Results for “optimization platform”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,333 records · Page 74

All sources NASA NTRS DOE OSTI

DOE OSTI2023

Light detection with power and signal transmission over fiber

The Deep Underground Neutrino Experiment is a next generation long baseline (1300 km) neutrino oscillation experiment. The neutrino beam measurements will be performed by a near detector and far detector. The far detector will consist of four modules, installed 1.5 km deep underground, based on Liquid Argon Time Projection Chamber (LArTPC) technology to detect particles. The Vertical Drift (VD) LArTPC is a recent technology proposed by the DUNE collaboration for the second FD module. In VD, light collection will be optimized by embedding photon detectors within the LArTPC cathode, which is biased at −300 kV. As a result, power must arrive to the Photon Detection System and signal must be transmitted via non-conductive material. The proposed solution is to use Power-over-Fiber and Signal-over-Fiber. An intense validation of the system is being performed by the collaboration at the CERN Neutrino Platform. The design of the system and the results of the validation collected over the first half of 2022 are presented here.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Compact fiber-coupled narrowband two-mode squeezed light source

Quantum correlated states of light, such as squeezed states, are a fundamental resource for the development of quantum technologies, as they are needed for applications in quantum metrology, quantum computation, and quantum communications. It is thus critical to develop compact, efficient, and robust sources to generate such states. Here, we report on a compact, narrowband, fiber-coupled source of two-mode squeezed states of light at 795 nm based on four-wave mixing (FWM) in an 85 Rb atomic vapor. The source is designed in a small modular form factor, with two input fiber-coupled beams, the seed and pump beams required for the FWM, and two output fibers, one for each of the modes of the squeezed state. The system is optimized for low pump power (135 mW) to achieve a maximum intensity-difference squeezing of 4.4 dB after the output of fibers at an analysis frequency of 1 MHz. Furthermore, the narrowband nature of the source makes it ideal for atomic-based quantum sensing and quantum networking configurations that rely on atomic quantum memories. Such a source paves the way for a versatile and portable platform for applications in quantum information science.

Jain, Umang [University of Oklahoma, Norman, OK (U↗

DOE OSTI2017

Computing Properties of Hadrons, Nuclei and Nuclear Matter from Quantum Chromodynamics

This project was part of a coordinated software development effort which the nuclear physics lattice QCD community pursues in order to ensure that lattice calculations can make optimal use of present, and forthcoming leadership-class and dedicated hardware, including those of the national laboratories, and prepares for the exploitation of future computational resources in the exascale era. The UW team improved and extended software libraries used in lattice QCD calculations related to multi-nucleon systems, enhanced production running codes related to load balancing multi-nucleon production on large-scale computing platforms, and developed SQLite (addressable database) interfaces to efficiently archive and analyze multi-nucleon data and developed a Mathematica interface for the SQLite databases.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

HPC-enabled computation of demand models at scale

The purpose of this project is to examine the energy impact of urban-scale traffic for the Los Angeles Basin by developing and implementing a scalable traffic assignment model. An energy optimization function will be posed and when integrated into the optimization code for travel assignment it can be mathematically proven to converge. The energy optimization function can then be compared to the typical travel time optimization that is traditionally used in traffic assignment models. The analysis will begin with static traffic assignment models with the routing for all origin and destinations computed in parallel on high performance computing facilities. Convergence of the numerical methods rely on the solution of convex programs (or extensions of these). This step will mostly consist of demonstrating the ability to parallelize the Frank Wolfe algorithm on various platforms.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

HPC4Mobilty w/ UCB

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

A Novel 'Smart Microchip Proppants' Technology for Precision Diagnostics of Hydraulic Fracture Networks (Edited Final Report)

This project introduces innovative technology to improve subsurface characterization, visualization, and diagnostics of unconventional reservoirs (fossil resources). Through a collaborative effort involving the University of Kansas, UCLA, MicroSilicon Inc., and EOG Resources, the project aims to deliver precision diagnostics for hydraulic fractures using novel high-resolution imaging technology based on smart microchip proppants. Additionally, it seeks to enhance the accuracy and predictability of integrated numerical, and machine-learning modeling techniques for hydraulic fracture characterization and simulation. This groundbreaking technology addresses significant gaps in understanding unconventional and tight reservoir behavior and optimizing well-completion strategies, enabling more cost-efficient recovery of unconventional resources.

02 PETROLEUM↗

DOE OSTI2020

Rapid and Simultaneous Characterization of Drug Conjugation in Heavy and Light Chains of a Monoclonal Antibody Revealed by High-Resolution Ion Mobility Separations in SLIM

Antibody-drug conjugates (ADCs) have recently gained traction in the biomedical community due to their promise for human therapeutics and an alternative to chemotherapy for cancer. Crucial metrics for ADC efficacy, safety, and selectivity are their drug-antibody ratios (DARs). However, DAR characterization (i.e., determining the average number of conjugated drugs on the antibody) through analytical methods remains challenging due to the heterogeneity of drug conjugation as well as the numerous post-translational modifications possible in the monoclonal antibody. In this work, we report on the use of high-resolution ion mobility spectrometry separations in our structures for lossless ion manipulations coupled to mass spectrometry (SLIM IMS-MS) platform for the rapid and simultaneous characterization of the drug load profile (i.e., stoichiometric distribution of the number of conjugated drugs present on the mAb), determination of the weighted average DAR in both the heavy and light chains of a model antibody-drug conjugate, and calculation of the overall DAR of the ADC. After chemical reduction of the ADC and a subsequent 31.5 meter SLIM IMS separation the various drug bound antibody species could be well resolved for both chains. Furthermore, we also show that higher resolution separations were possible with SLIM IMS as compared to ones performed on a commercially available (~1 meter) drift tube IMS-MS platform. Interestingly, additional gas-phase substructures become evident with longer path length SLIM IMS, potentially providing insight related to how drug conjugation may alter the structural properties of a monoclonal antibody and thus affect its overall potency and/or selectivity for a given antigen. We expect high-resolution SLIM IMS separations will augment the existing toolbox for ADC characterization, particularly for structural confirmation to enable the rapid optimization of DAR for a given ADC and thus better understand its potential toxicity and potency.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

Limits to the Optical Response of Graphene and Two-Dimensional Materials

Two-dimensional (2D) materials provide a platform for strong light–matter interactions, creating wide-ranging design opportunities via new-material discoveries and new methods for geometrical structuring. Here we derive general upper bounds to the strength of such light–matter interactions, given only the optical conductivity of the material, including spatial nonlocality, and otherwise independent of shape and configuration. Our material figure-of-merit shows that highly doped graphene is an optimal material at infrared frequencies, whereas single-atomic-layer silver is optimal in the visible. For quantities ranging from absorption and scattering to near-field spontaneous-emission enhancements and radiative heat transfer, we consider canonical geometrical structures and show that in certain cases the bounds can be approached, while in others there may be significant opportunity for design improvement. The bounds can encourage systematic improvements in the design of ultrathin broadband absorbers, 2D antennas, and near-field energy harvesters.

2D materials↗

DOE OSTI2022

Multiplexed Anodic Stripping Voltammetry Detection of Heavy Metals in Water Using Nanocomposites Modified Screen-Printed Electrodes Integrated With a 3D-Printed Flow Cell

In this study, we present multiplexed anodic stripping voltammetry (ASV) detection of heavy metal ions (HMIs)—As(III), Cd(II), and Pb(II)—using a homemade electrochemical cell consisting of dual working, reference and counter screen-printed electrodes (SPE) on polyimide substrate integrated with a 3D-printed flow cell. Working and counter electrodes were fabricated by the screen-printing of graphite paste while the Ag/AgCl paste was screen-printed as a reference electrode (Ag/AgCl quasi-reference electrode). The working electrodes were modified with (BiO) 2 CO 3 -reduced graphene oxide (rGO)-Nafion [(BiO) 2 CO 3 -rGO-Nafion] and Fe 3 O 4 magnetic nanoparticles (Fe 3 O 4 MNPs) decorated Au nanoparticles (AuNPs)-ionic liquid (IL) (Fe 3 O 4 -Au-IL) nanocomposites separately to enhance HMIs sensing. Electrochemical detection was achieved using square wave ASV technique. The desired structure of the flow electrochemical cell was optimized by the computational fluid dynamic (CFD). Different experimental parameters for stripping analysis of HMIs were optimized including deposition time, deposition potential and flow rate. The linear range of calibration curves with the sensing nanocomposites modified SPE for the three metal ions was from 0–50 μg/L. The limits of detection (S/N = 3) were estimated to be 2.4 μg/L for As(III), 1.2 μg/L for Pb(II) and 0.8 μg/L for Cd(II). Furthermore, the homemade flow anodic stripping sensor platform was used to detect HMIs in simulated river water with a 95–101% recovery, indicating high selectivity and accuracy and great potential for applicability even in complex matrices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Utilizing a Novel Acoustic Backscatter Array to Characterize Waste Consolidation and Settling in a Horizontal Flow Clarifier - 16051

As part of a collaboration between the University of Leeds, Sellafield Ltd and MMI Engineering Ltd, bespoke acoustic instrumentation and numerical simulation methods have been established to optimize nuclear legacy waste transfers. Specifically, a new ultrasonic measurement system has been developed, allowing suspended particle concentration and consolidation to be measured remotely. This technology has been combined with computational fluid dynamics (CFD) modelling of settling particulate systems, permitting full characterization, simulation and prediction of sludge separation processes. Presented here are experimental and numerical results on the transport and settling behavior of non-active nuclear-analogue suspensions in two flow geometries: gravitational settling of glass dispersions in a 250-liter column; and transport and sedimentation of flocculated calcite in a close-to-full-scale clarifier (9 m{sup 3} total volume and 4.8 m{sup 2} length). In addition, details of the design, construction and calibration of a custom-built Ultrasonic Array Research Platform (UARP) are described. Settling column results suggested that particle concentration changes could be simulated with good accuracy by a CFD model (developed using the open source OpenFOAM framework) when compared to measured samples. Large-scale clarifier trials were used to assess the effectiveness of the UARP controller with an attached in situ acoustic backscatter array (ABA). The ABA consisted of 8 transducers angled down at 20 deg. to the vertical, pulsing at 2-2.5 MHz in cycles (covering 1.8 m total depth). In comparison to a range of sampled concentrations across the length of the clarifier, results confirmed that the UARP-ABA system was highly successful at characterizing these complex flows over several hours of operation, allowing visualization of depth-wise bulk density changes and bed build-up over time. Collectively, this work highlights the capability of these tools to monitor and optimize a number of current waste transfer operations at Sellafield, with further potential applications for solid-liquid separations across waste, water treatment and minerals engineering industries. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2019

Machine Learning Applied to a Variable Charge Atomistic Model for Cu/Hf Binary Alloy Oxide Heterostructures [Machine Learning a Variable Charge Atomistic Model for Cu/Hf Binary Alloy Oxide Heterostructures]

Alloy oxide heterostructures are essential for a wide variety of energy applications, including anticorrosion coatings, bifunctional catalysis, energy storage, as well as emerging platforms for multilevel nonvolatile memory and neuromorphic devices. The key role played by oxide composition, density, and stoichiometry in governing electrochemical reactions, interface structure, and ionic transport in alloy oxides remains largely unknown. This is primarily due to the lack of variable charge interatomic potential models that can adequately describe the various atomic/ionic interactions in alloy oxides within a unified framework. Here, we introduce a charge transfer ionic potential (CTIP) model for Cu/Hf/O alloy system and demonstrate its ability to accurately capture the complex potential energy surface owing to dynamically varying interactions, including metallic (Cu/Hf), ionic (Cu/Hf/Ox), mixed environment (interfaces). We leverage supervised machine learning methods powered by genetic algorithms coupled with local simplex optimization to efficiently navigate through a high-dimensional parameter space and identify an optimum set of an independent set of CTIP parameters. We train our model against an extensive first-principles based data set that includes lattice constants, cohesive energies, equations of state, and elastic constants of various experimentally observed polymorphs of hafnia, copper oxide, hafnium, as well as copper. Our machine-learned CTIP model captures the structure, elastic properties, thermodynamics, and energetic ordering of various polymorphs. It also accurately predicts the surface properties of both oxides and their metals. To demonstrate the suitability of our CTIP model for investigating dynamic processes, we employed it to identify the atomistic scale mechanisms associated with the initial nanoscale oxidation and surface oxide growth on Cu-doped hafnia surfaces. Here, our machine-learned CTIP model can be used to probe the dynamic response of Cu/Hf/O alloy interfaces subjected to external stimuli (e.g., electric field, pressure, temperature, strain, etc.) and a variety of atomistic phenomena including the dynamics of switching in emerging neuromorphic platforms.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Iodine-Containing Mass-Defect-Tuned Dendrimers for Use as Internal Mass Spectrometry Calibrants

Calibrants based on synthetic dendrimers have been recently proposed as a versatile alternative to peptides and proteins for both MALDI and ESI mass spectrometry calibration. Because of their modular synthetic platform, dendrimer calibrants are particularly amenable to tailoring for specific applications. Utilizing this versatility, a set of dendrimers has been designed as an internal calibrant with a tailored mass defect to differentiate them from the majority of natural peptide analytes. This was achieved by incorporating a tris-iodinated aromatic core as an initiator for the dendrimer synthesis, thereby affording multiple calibration points (m/z range 600–2300) with an optimized mass-defect offset relative to all peptides composed of the 20 most common proteinogenic amino acids. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2016

Modular Homogeneous Chromophore–Catalyst Assemblies

Photosynthetic reaction center (RC) proteins convert incident solar energy to chemical energy through a network of molecular cofactors which have been evolutionarily tuned to couple efficient light-harvesting, directional electron transfer, and long-lived charge separation with secondary reaction sequences. These molecular cofactors are embedded within a complex protein environment which precisely positions each cofactor in optimal geometries along efficient electron transfer pathways with localized protein environments facilitating sequential and accumulative charge transfer. By contrast, it is difficult to approach a similar level of structural complexity in synthetic architectures for solar energy conversion. However, by using appropriate self-assembly strategies, we anticipate that molecular modules, which are independently synthesized and optimized for either light-harvesting or redox catalysis, can be organized into spatial arrangements that functionally mimic natural photosynthesis. In this Account, we describe a modular approach to new structural designs for artificial photosynthesis which is largely inspired by photosynthetic RC proteins. We focus on recent work from our lab which uses molecular modules for light-harvesting or proton reduction catalysis in different coordination geometries and different platforms, spanning from discrete supramolecular assemblies to molecule–nanoparticle hybrids to protein-based biohybrids. Molecular modules are particularly amenable to high-resolution characterization of the ground and excited state of each module using a variety of physical techniques; such spectroscopic interrogation helps our understanding of primary artificial photosynthetic mechanisms. In particular, we discuss the use of transient optical spectroscopy, EPR, and X-ray scattering techniques to elucidate dynamic structural behavior and light-induced kinetics and the impact on photocatalytic mechanism. Two different coordination geometries of supramolecular photocatalyst based on the [Ru(bpy)3]2+ (bpy = 2,2'-bipyridine) light-harvesting module with cobaloxime-based catalyst module are compared, with progress in stabilizing photoinduced charge separation identified. These same modules embedded in the small electron transfer protein ferredoxin exhibit much longer charge-separation, enabled by stepwise electron transfer through the native [2Fe-2S] cofactor. We anticipate that the use of interchangeable, molecular modules which can interact in different coordination geometries or within entirely different structural platforms will provide important fundamental insights into the effect of environment on parameters such as electron transfer and charge separation, and ultimately drive more efficient designs for artificial photosynthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

Electronic transport properties of one dimensional lithium nanowire using density functional theory

Single nanowire electrode devices are a unique platform for studying as energy storage devices. Lithium nanowire is of much importance in lithium ion batteries and therefore has received a great deal of attention in past few years. In this paper we investigated structural and electronic transport properties of Li nanowire using density functional theory (DFT) with SIESTA code. Electronic transport properties of Li nanowire are investigated theoretically. The calculations are performed in two steps: first an optimized geometry for Li nanowire is obtained using DFT calculations, and then the transport relations are obtained using NEGF approach. SIESTA and TranSIESTA simulation codes are used in the calculations correspondingly. The electrodes are chosen to be the same as the central region where transport is studied, eliminating current quantization effects due to contacts and focusing the electronic transport study to the intrinsic structure of the material. By varying chemical potential in the electrode regions, an I-V curve is traced which is in agreement with the predicted behavior. Agreement of bulk properties of Li with experimental values make the study of electronic and transport properties in lithium nanowires interesting because they are promising candidates as bridging pieces in nanoelectronics. Transmission coefficient and V-I characteristic of Li nano wire indicates that Li nanowire can be used as an electrode device.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

End-to-End Workflow for Machine-Learning-Based Qubit Readout With QICK and hls4ml

In this article, we present an end-to-end workflow for superconducting qubit readout that embeds codesigned neural networks into the quantum instrumentation control kit (QICK). Capitalizing on the custom firmware and software of the QICK platform, which is built on Xilinx radiofrequency system-on-chip field-programmable gate arrays (FPGAs), we aim to leverage machine learning (ML) to address critical challenges in qubit readout accuracy and scalability. The workflow utilizes the hls4ml package and employs quantization-aware training to translate ML models into hardware-efficient FPGA implementations via user-friendly Python application programming interfaces. We experimentally demonstrate the design, optimization, and integration of an ML algorithm for single transmon qubit readout, achieving 96% single-shot fidelity with a latency of 32.25 ns and less than 16% FPGA lookup table resource utilization. Our results offer the community an accessible workflow to advance ML-driven readout and adaptive control in quantum information processing applications.

42 ENGINEERING↗

DOE OSTI2021

Synchronous and Concurrent Multidomain Computing Method for Cloud Computing Platforms

We present a numerical method for synchronous and concurrent solution of transient elastodynamics problem where the computational domain is divided into subdomains that may reside on separate computational platforms. Here, this work employs the variational multiscale discontinuous Galerkin (VMDG) method to develop interdomain transmission conditions for transient problems. The fine-scale modeling concept leads to variationally consistent coupling terms at the common interfaces. The method admits a large class of time discretization schemes, and decoupling of the solution for each subdomain is achieved by selecting any explicit algorithm. Numerical tests with a manufactured solution problem show optimal convergence rates. The energy history in a free vibration problem is in agreement with that of the solution from a monolithic computational domain.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Data from Development of a CRISPR/Cas9-Based Tool for Gene Deletion in Issatchenkia orientalis

The nonconventional yeast Issatchenkia orientalis has emerged as a potential platform microorganism for production of organic acids due to its ability to grow robustly under highly acidic conditions. However, lack of efficient genetic tools remains a major bottleneck in metabolic engineering of this organism. Here we report that the autonomously replicating sequence (ARS) from Saccharomyces cerevisiae (ScARS) was functional for plasmid replication in I. orientalis , and the resulting episomal plasmid enabled efficient genome editing by the CRISPR/Cas9 system. The optimized CRISPR/Cas9-based system employed a fusion RPR1′-tRNA promoter for single guide RNA (sgRNA) expression and could attain greater than 97% gene disruption efficiency for various gene targets. Additionally, we demonstrated multiplexed gene deletion with disruption efficiencies of 90% and 47% for double gene and triple gene knockouts, respectively. This genome editing tool can be used for rapid strain development and metabolic engineering of this organism for production of biofuels and chemicals.

Conversion↗

DOE OSTI2022

Hydrogen Storage for Flexible Fossil Fuel Power Generation: Integration of Underground Hydrogen Storage with Gas Turbine (Final Report)

As the nation continues to encourage, through market structures and financial incentives, the proliferation of intermittent renewable electricity, how to optimize the ever-changing electric grid and identify means to retain and improve resilience, while ensuring continued reductions in GHG emissions, will be critical. According to Bloomberg, wind & solar generated 10.5% of US electricity in 2020 and that percentage continues to grow. In support of expanding renewable energy use, and to address its intermittent nature, this project will develop the Hydrogen Storage for Flexible Fossil Fuel Power Generation platform that is dispatchable, reliable, repeatable and have the ability to produce zero or negative carbon power while interfacing with geology capable of CO2 and hydrogen storage. GTI Energy (GTIE) and team members Illinois State Geological Survey (ISGS), Mitsubishi Heavy Industries America (MHIA), Ameren Illinois, Hexagon Purus, and the Low Carbon Resources Initiative (LCRI) completed a Phase I Conceptual Study under contract DE-FE0032012 for Hydrogen Storage for Flexible Fossil Fuel Power Generation: Integration of Underground Hydrogen Storage with Gas Turbine. The Hydrogen Storage for Flexible Fossil Fuel Power Generation platform addresses the intermittent nature of the expanding use of Variable Renewable Energy (VRE) generation. The low cost of the electricity (COE) generated results in greater dispatch and more operation at higher power levels (higher efficiency), fewer short intervals, and fewer start/stop cycles. The reliable, resilient system can produce zero carbon power and store hydrogen. It will demonstrate hydrogen storage in geologic formations like those used in natural gas underground storage thus enabling large scale storage of hydrogen in sedimentary strata across the United States rather than in geographically restricted salt caverns. The Phase I study confirmed the system is feasible and generates power at lower cost than other low carbon approaches. The demonstration defines the pathway for broad commercial application and will accelerate the development of larger systems suitable for centralized utility scale electricity production. The study advanced the maturity of the H 2 storage-based system with flexible power generation by completing a Pre-FEED study (Phase II). The Pre-FEED focused on the selected Energy Farm on the University of Illinois Urbana-Champaign (UIUC) site that includes above ground and underground hydrogen storage, low-carbon hydrogen production (GTI’s Compact Hydrogen Generator, CHG) with underground CO2 sequestration, and a 40-MW class gas turbine. The Pre-FEED addressed the entire system and its interconnection to the natural gas and electric grid and mitigation of key risks, such as storage behavior, load-following, and system operation. During Phase 1 of the project, the team completed key tasks, which moved the entire demonstration project, specific components and approaches closer to commercialization. These Phase I Accomplishments include: Completing System Requirements Review; Completing System Layout and Modeling - Heat & Mass Balance and Process Flow Diagram; Completing modelling of 9 turbine performance cases; Evaluating rock strata for underground storage of hydrogen and sequestration of carbon dioxide; Completing initial modelling of underground storage of hydrogen and withdrawal with evaluation of loss and water production; Identifying roadable storage for above ground hydrogen storage; Identifying existing electrical infrastructure for receiving/delivering electricity; Identifying existing gas supply infrastructure for receiving natural gas; Document concept design/development plans in required reports. Conclusions: The 12-month Feasibility study in Phase I study was completed and confirmed the system is feasible and generates power at lower cost than other low carbon approaches and even lower cost than the reference NGCC plant without carbon capture when taking advantage of 45Q carbon credits. The study enabled the fidelity of the concept to be improved and allowed identification of the requirements for the system. Defining the individual system and component requirements was performed via the system requirements review with the whole team. These requirements were then incorporated into and iterated with our Heat & Mass Balance process model and process flow diagrams were generated to reflect the overall system. This information was then used to complete the TEA and show economic feasibility. Large scale non-salt geologic storage of hydrogen is an enabling technology for a hydrogen-fired turbine that can be retrofitted into large-scale electric generating units (EGU). Our demonstration will include 428 MWh or ~4 hours full load of hydrogen storage (above and underground). Carbon capture inherent to the CHG process can capture 90% CO 2 (with upgrades to >98%). This system provides a COE of 23% savings relative to an NGCC with a post combustion amine system. Our proposed storage system decouples carbon capture and hydrogen production from power production; therefore, we expect our proposed system’s efficiency and variable COE to be superior resulting in overall higher dispatch and reduced deep cycling. Our demonstration will be full to multi-day hydrogen storage and has the potential for longer (seasonal) duration commercially. The demonstration defines the pathway for broad commercial application and will accelerate the development of larger systems suitable for centralized utility scale electricity production.

03 NATURAL GAS↗