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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Short-range correlations control the G/K and Poisson ratios of amorphous solids and metallic glasses

The bulk modulus of many amorphous materials, such as metallic glasses, behaves nearly in agreement with the assumption of affine deformation, namely that the atoms are displaced just by the amount prescribed by the applied strain. In contrast, the shear modulus behaves as for nonaffine deformations, with additional displacements due to the structural disorder which induce a marked material softening to shear. The consequence is an anomalously large ratio of the bulk modulus to the shear modulus for disordered materials characterized by dense atomic packing, but not for random networks with point atoms. We explain this phenomenon with a microscopic derivation of the elastic moduli of amorphous solids accounting for the interplay of nonaffinity and short-range particle correlations due to excluded volume. Short-range order is responsible for a reduction of the nonaffinity which is much stronger under compression, where the geometric coupling between nonaffinity and the deformation field is strong, whilst under shear this coupling is weak. Predictions of the Poisson ratio based on this model allow us to rationalize the trends as a function of coordination and atomic packing observed with many amorphous materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Many-body expansion based machine learning models for octahedral transition metal complexes

Abstract Graph-based machine learning (ML) models for material properties show great potential to accelerate virtual high-throughput screening of large chemical spaces. However, in their simplest forms, graph-based models do not include any 3D information and are unable to distinguish stereoisomers such as those arising from different orderings of ligands around a metal center in coordination complexes. In this work we present a modification to revised autocorrelation descriptors, a molecular graph featurization method, for predicting spin state dependent properties of octahedral transition metal complexes (TMCs). Inspired by analytical semi-empirical models for TMCs, the new modeling strategy is based on the many-body expansion (MBE) and allows one to tune the captured stereoisomer information by changing the truncation order of the MBE. We present the necessary modifications to include this approach in two commonly used ML methods, kernel ridge regression and feed-forward neural networks. On a test set composed of all possible isomers of binary TMCs, the best MBE models achieve mean absolute errors (MAEs) of 2.75 kcal mol −1 on spin-splitting energies and 0.26 eV on frontier orbital energy gaps, a 30%–40% reduction in error compared to models based on our previous approach. We also observe improved generalization to previously unseen ligands where the best-performing models exhibit MAEs of 4.00 kcal mol −1 (i.e. a 0.73 kcal mol −1 reduction) on the spin-splitting energies and 0.53 eV (i.e. a 0.10 eV reduction) on the frontier orbital energy gaps. Because the new approach incorporates insights from electronic structure theory, such as ligand additivity relationships, these models exhibit systematic generalization from homoleptic to heteroleptic complexes, allowing for efficient screening of TMC search spaces.

Meyer, Ralf (ORCID:0000000322360261)↗
DOE OSTI2014

A Scalable Solution Framework for Stochastic Transmission and Generation Planning Problems. Draft

Current commercial software tools for transmission and generation investment planning have limited stochastic modeling capabilities. Because of this limitation, electric power utilities generally rely on scenario planning heuristics to identify potentially robust and cost effective investment plans for a broad range of system, economic, and policy conditions. Several research studies have shown that stochastic models perform significantly better than deterministic or heuristic approaches, in terms of overall costs. However, there is a lack of practical solution approaches to solve such models. In this paper we propose a scalable decomposition algorithm to solve stochastic transmission and generation planning problems, respectively considering discrete and continuous decision variables for transmission and generation investments. Given stochasticity restricted to loads and wind, solar, and hydro power output, we develop a simple scenario reduction framework based on a clustering algorithm, to yield a more tractable model. The resulting stochastic optimization model is decomposed on a scenario basis and solved using a variant of the Progressive Hedging (PH) algorithm. We perform numerical experiments using a 240-bus network representation of the Western Electricity Coordinating Council in the US. Although convergence of PH to an optimal solution is not guaranteed for mixed-integer linear optimization models, we find that it is possible to obtain solutions with acceptable optimality gaps for practical applications. Our numerical simulations are performed both on a commodity workstation and on a high-performance cluster. The results indicate that large-scale problems can be solved to a high degree of accuracy in at most two hours of wall clock time.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2009

The Lunar Quest Program and the International Lunar Network (ILN)

The Lunar and Planetary Science group at Marshall provides core capabilities to support the Agency's lunar exploration goals. ILN Anchor Nodes are currently in development by MSFC and APL under the Lunar Quest Program at MSFC. The Science objectives of the network are to understand the interior structure and composition of the moon. Pre-phase A engineering assessments are complete, showing a design that can achieve the science requirements, either on their own (if 4 launched) or in concert with international partners. Risk reduction activities are ongoing. The Lunar Quest Program is a Science-based program with the following goals: a) Fly small/medium science missions to accomplish key science goals; b) Build a strong lunar science community; c) Provide opportunities to demonstrate new technologies; and d) Where possible, help ESMD and SOMG goals and enhance presence of science in the implementation of the VSE. The Lunar Quest Program will be guided by recommendations from community reports.

Cohen, Barbara A.↗
NASA NTRSDate not supplied

Ab initio ground states of strongly-correlated materials on quantum computers

The accurate first-principles description of strongly-correlated materials is an important and challenging problem in condensed matter physics. Ab initio downfolding has emerged as a way of deriving accurate many-body Hamiltonians including strong correlations, representing a subspace of interest of a material, using density functional theory calculations as a starting point. However, the solution of these material-specific models can scale exponentially on classical computers, constituting a challenge. Here we propose that utilizing quantum computers for obtaining the properties of downfolded Hamiltonians yields an accurate description of the ground state properties of strongly-correlated systems, while circumventing the exponential scaling problem. We benchmark the solution of Hubbard-like models obtained through downfolding by utilizing a classical tensor network implementation of variational quantum eigensolvers (VQE), and we reveal a strategy for driving the optimization through a hybrid minimization of the energy and maximization of the overlap with an approximate solution obtained through low-cost computational methods. This results in a reduction of the energy error by orders of magnitude compared to conventional VQE approaches, and allows us to reproduce long-range correlations for the first time. We demonstrate our first-principles approach for diverse strongly-correlated materials, correctly predicting the antiferromagnetic state of one-dimensional cuprate Ca 2 CuO 3 , the excitonic ground state of monolayer WTe2, and the charge-ordered state of correlated metal SrVO 3 . Our efficient computational implementation allows us to simulate large systems with up to 54 qubits and encompassing up to four correlated bands, which is indicative of the complexity that our framework can address.

Antonios M Alvertis↗
DOE OSTI2024

Synthesis of hierarchical graphene coated porous Si anode for lithium-ion batteries

The ultra-high capacity and widespread availability of Si materials have resulted in them being the focus of extensive studies to replace the graphite anode. However, the main barriers preventing the Si anodes from large-scale applications are their huge volume change and severe interface reactions in the lithiation/delithiation process, which pulverizes its structure and subsequently deteriorates its cycle life. Here, micrometer-scale porous Si coated with graphene coating (mpSi@G) has been synthesized by using SiO 2 nanoparticles and novel coal-derived humic acid as feedstocks through a magnesiothermic reduction, followed by spray drying and calcination techniques. SEM, Raman, and X-ray absorption analysis demonstrate that the hierarchical graphene shell and micrometer-sized porous Si structure effectively release the Si anode's mechanical stress upon lithiation to achieve good structural stability. Here, the synthesized mpSi@G anode delivers a high initial lithiation capacity of 2974.9 mAh g –1 at 0.1 A g –1 with an initial coulombic efficiency of 70.2 %. Furthermore, the conductive hierarchical graphene network, along with the tight contacts of porous-Si and the graphene shell, contribute to a high capacity of 1109.5 mAh g –1 at a high current density of 5.0 A g –1 , showing excellent rate capability.

25 ENERGY STORAGE↗
DOE OSTI2023

Machine learning based simultaneous control of air handling unit discharge air and condenser water temperatures set-point for minimized cooling energy in an office building

In this study, an artificial intelligence based real-time prediction and control model to optimize condenser water temperature and discharge air temperature (DAT) set-points in water-cooled air handling unit (AHU) system has been developed. EnergyPlus-MATLAB co-simulation has been conducted to analyze the developed model's effectiveness. Here, to develop artificial neural networks (ANN) model, embedded neural network objects in MATLAB was utilized. The developed model could decide an optimal temperature set-points based on outdoor air wet-bulb temperature to reflect the Korean climate context. As a result, the developed ANN prediction model showed the predictive performance of Cv(RMSE) of approximately 21%. Compared to the conventional fixed temperature algorithm, which fixes AHU DAT at 14°C and condenser water temperature at 32°C, the ANN based optimized control showed a 22% total cooling energy reduction. These results show that significant energy savings can be achieved by simultaneously controlling condenser water temperature and AHU DAT set-points considering Korean climatic characteristics using AI technologies such as ANN models.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Resolving the kinetics of individual aqueous reaction steps of actinyl (AnO 2 + and AnO 2 2+ ; An=U, Np, and Pu) tricarbonate complexes with ferrous iron and hydrogen sulfide from first principles

The solubility and mobility of actinides (An), like uranium, neptunium, and plutonium, in the environment largely depends on their oxidation states. Actinyls (An V,VI O 2 +/2+ (aq) ) form strong complexes with available ligands, like carbonate (CO 3 2- ), which may inhibit reduction to relatively insoluble An IV O 2(s) . Here we use quantum-mechanical calculations to explore the kinetics of aqueous homogeneous reaction paths of actinyl tricarbonate complexes ([AnO 2 (CO 3 ) 3 ] 5-/4- ) with two different reductants, [Fe(OH) 2 (H 2 O) 4 ] 0 and [H 2 S(H 2 O) 6 ] 0 . Energetically-favorable outer-sphere complexes (OSC) are found to form rapidly, on the order of milliseconds to seconds over a wide actinyl concentration range (pM to mM). The systems then encounter energy barriers ( E a ), some of which are prohibitively high (>100 kJ/mol for some neptunyl and plutonyl reactions with Fe 2+ and H 2 S), that define the transition from outer- to inner-sphere complex (ISC; for example, calculated E a of ISC formation between UO 2 + and UO 2 2+ with Fe 2+ are 35 and 74 kJ/mol, respectively). In some reactions, multiple OSCs are observed that represent different hydrogen bonding networks between solvent molecules and carbonate. Even when forming ISCs, electron transfer to reduce An 6+ and An 5+ is not observed (no change in atomic spin values or lengthening of An–O ax bond distances). Proton transfer from bicarbonate and water to actinyl O was tested as a mechanism for electron transfer from Fe 2+ to U 6+ and Pu 6+ . Not all proton transfer reactions yielded reduction of An 6+ to An 5+ and only a few pathways were energetically-favorable (e. g. H + transfer from H 2 O to drive Pu 6+ reduction to Pu 5+ with Δ E = -5 kJ/mol). The results suggest that the tricarbonate complex serves as an effective shield against actinide reduction in the tested reactions and will maintain actinyl solubility at elevated pH conditions. The results highlight reaction steps, such as inner-sphere complex formation and electron transfer, which may be rate-limiting. Thus, this study may serve as the basis for future research on how they can be catalyzed by a mineral surface in a heterogeneous process.

Chemistry↗
DOE OSTI2026

Thermoelectric heating and cooling–integrated dishwasher with thermal energy storage

Household dishwashers must address several performance goals: maximize washing and drying performance, while minimizing cycle duration, energy consumption, and water consumption. This study develops and examines a novel thermoelectric heating and cooling (TEHC) system with thermal energy storage applied to a household dishwasher (DW), aiming to improve the energy and drying performance of a commercially-available dishwasher while maintaining its washing performance, water consumption, and cycle duration. Experimental testing conducted on the novel TEHC-DW system demonstrates an 8.7% reduction in total energy consumption, lowering the per-cycle usage to 0.952 kWh, and a 40% reduction in energy consumption for internal water heating. The novel TEHC-DW system also demonstrates better drying performance, shortening the drying time by 42% to reach the same remaining moisture content as a commercially-available system. In addition, a resistance-capacitance network model is developed that predicts total drying time, total energy consumption, and the highest temperature reached in the tub (53.4 °C). The model accuracy is validated with experimental data (within ±1 K), and the model functions as a design tool via a parametric study to evaluate the next-generation design and the effect of the number of thermoelectric modules and thermoelectric driving force (i.e., current). Overall, this study demonstrates the potential for TEHC technology to improve energy efficiency and drying performance in household dishwashers.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Quantifying biogeochemical heterogeneity in soil systems

Soils are increasingly perceived as complex systems with properties and biogeochemical functions that vary on millimeter scales. Quantitative information about the resulting biogeochemical heterogeneity is needed to improve process knowledge and to render biogeochemical models more mechanistic. Here in this work, we demonstrate how standardized arrays of Pt-electrodes can be used to quantify biogeochemical or ‘functional’ soil heterogeneity, defined as the extent to which the soil is subdivided into microenvironments. Our case study confirmed the validity of this approach for a soil sequence consisting of a well-drained, a moderately well drained and a poorly drained Mollisol. We found that (i) variations in soil moisture content are the immediate cause for variations in functional heterogeneity, with (ii) soil porosity influencing rates and the magnitude of change. We posit that the deployment of standardized arrays of Pt-electrodes will offer an affordable option to monitor the general metabolic state of the soil system and simultaneously quantify the functional heterogeneity of underlying processes at any point in time. Such information should be useful to improve quantitative estimates of processes as diverse as trace gas emissions, trace gas consumption, reductive dehalogenation and mobilization of metals in the subsurface biosphere. Lastly, we recommend that parameterization of functional soil heterogeneity be included in long-term soil monitoring programs such as Superfund Sites, Critical Zone Observatories, Long Term Ecological Research (LTER) and National Ecological Observatory Network (NEON) sites.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Loss circulation prevention in geothermal drilling by shape memory polymer

Geothermal formations are naturally fractured with large fracture openings and networks. This can often lead to frequent drilling fluid loss events which is a major contributor to the cost and non-productive time in geothermal drilling. Development of smarter technologies and methods to tackle problem lost circulation is vital for geothermal drilling cost reduction required for geothermal energy to be recognized as a competitive alternative energy source. Mitigation of this problem and other drilling problems such as stuck pipe can minimize overall project cost. In this report, a thermoset shape memory polymer that can be activated by formation natural heat was assessed to seal near wellbore fractures in geothermal wells. The performance of the shape memory polymer (SMP) was evaluated using artificial fractures created in aluminum discs and cylindrical granite cores. Rheology and particle size distribution were considered. A novel testing setup was built for this work, which allows testing of sealing efficiency under dynamic conditions at high temperature. Analysis showed that the SMP has efficiently succeeded in forming a strong plug inside the fractures and stopped fluid loss at high sealing pressure. This smart loss circulation material can expand within the fractures to reduces non-drilling time and strengthen the wellbore in high-temperature drilling operations.

58 GEOSCIENCES↗
DOE OSTI2014

Enhanced electrocatalytic activity of the Au-electrodeposited Pt nanoparticles-coated conducting oxide for the quantum dot-sensitized solar cells

Au was electrodeposited potentiostatically at 0.3 V for 5 min on nanoporous Pt nanoparticle-coated F-doped SnO{sub 2} (FTO/Pt) substrates. For comparison, Au-electrodeposited FTO (FTO/Au) and Au-uncoated FTO/Pt were prepared. FTO/Au showed large-sized Au clusters dispersed sparsely over FTO, which resulted in lower electrocatalytic activity than FTO/Pt. In contrast, FTO/Pt exhibited poor stability unlike FTO/Au due to poisoning by the adsorption of sulfur species. The Au-electrodeposited FTO/Pt (FTO/Pt/Au) consisted of small Au clusters deposited over the entire area of Pt due to the effective Au nucleation provided by nanoporous metallic Pt. FTO/Pt/Au exhibited enhanced electrocatalytic activity and excellent stability because the small Au particles well-dispersed over the nanoporous metallic Pt network provided numerous electrochemical reaction sites, and the Pt surface was not exposed to the electrolyte. When FTO/Pt/Au was used as the counter electrode (CE) of a quantum dot-sensitized solar cell, the significantly enhanced electrocatalytic activity of the FTO/Pt/Au CE facilitated the reduction reaction of S{sub n}{sup 2− }+ 2e{sup −} (CE) → S{sub n−1}{sup 2−} + S{sup 2−} at the CE/electrolyte interface, resulting in a significantly hindered recombination reaction, S{sub n}{sup 2− }+ 2e{sup −} (TiO{sub 2} in the photoanode) → S{sub n-1}{sup 2−} + S{sup 2−}, and significantly improved overall energy conversion efficiency.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Multiscale Flow for robust and optimal cosmological analysis

We propose Multiscale Flow, a generative Normalizing Flow that creates samples and models the field-level likelihood of two-dimensional cosmological data such as weak lensing. Multiscale Flow uses hierarchical decomposition of cosmological fields via a wavelet basis and then models different wavelet components separately as Normalizing Flows. The log-likelihood of the original cosmological field can be recovered by summing over the log-likelihood of each wavelet term. This decomposition allows us to separate the information from different scales and identify distribution shifts in the data such as unknown scale-dependent systematics. The resulting likelihood analysis can not only identify these types of systematics, but can also be made optimal, in the sense that the Multiscale Flow can learn the full likelihood at the field without any dimensionality reduction. We apply Multiscale Flow to weak lensing mock datasets for cosmological inference and show that it significantly outperforms traditional summary statistics such as power spectrum and peak counts, as well as machine learning–based summary statistics such as scattering transform and convolutional neural networks. We further show that Multiscale Flow is able to identify distribution shifts not in the training data such as baryonic effects. Finally, we demonstrate that Multiscale Flow can be used to generate realistic samples of weak lensing data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Potential Cooling Energy Savings of Economizer Control and Artificial-Neural-Network-Based Air-Handling Unit Discharge Air Temperature Control for Commercial Building

Heating, ventilation, and air-conditioning (HVAC) systems play a significant role in building energy consumption, accounting for around 50% of total energy usage. As a result, it is essential to explore ways to conserve energy and improve HVAC system efficiency. One such solution is the use of economizer controls, which can reduce cooling energy consumption by using the free-cooling effect. However, there are various types of economizer controls available, and their effectiveness may vary depending on the specific climate conditions. To investigate the cooling energy-saving potential of economizer controls, this study employs a dry-bulb temperature-based economizer control approach. The dry-bulb temperature-based control strategy uses the outdoor air temperature as an indicator of whether free cooling can be used instead of mechanical cooling. This study also introduces an artificial neural network (ANN) prediction model to optimize the control of the HVAC system, which can lead to additional cooling energy savings. To develop the ANN prediction model, the EnergyPlus program is used for simulation modeling, and the Python programming language is employed for model development. The results show that implementing a temperature-based economizer control strategy can lead to a reduction of 7.6% in annual cooling energy consumption. Moreover, by employing an ANN-based optimal control of discharge air temperature in air-handling units, an additional 22.1% of cooling energy savings can be achieved. In conclusion, the findings of this study demonstrate that the implementation of economizer controls, especially the dry-bulb temperature-based approach, can be an effective strategy for reducing cooling energy consumption in HVAC systems. Additionally, using ANN prediction models to optimize HVAC system controls can further increase energy savings, resulting in improved energy efficiency and reduced operating costs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

Insights on the Study of Nafion Nanoscale Morphology by Transmission Electron Microscopy

Nafion is one of the most common materials used for polyelectrolyte membranes and is the standard to which novel materials are compared. In spite of great interest in Nafion’s nanostructure, it is still a subject of controversy. While multiple research efforts have addressed Nafion’s morphology with Transmission Electron Microscopy, the results of these efforts have often been inconsistent and cannot satisfactorily describe the membrane structure. One of the reasons for differences in the reported results is the lack of sufficient control over the damage caused by electron beam irradiation. In this work, we describe some aspects of damage in the material that have a strong influence on the results. We show that irradiation causes mass loss and phase separation in the material and that the morphologies that have been observed are, in many cases, artifacts caused by damage. We study the effect of the sample temperature on damage and show that, while working at low temperature does not prevent damage and mass loss, it slows formation of damage-induced artifacts to the point where informative low-dose images of almost undamaged material may be collected. We find that charging of the sample has a substantial effect on the damage, and the importance of charge neutralization under irradiation is also seen by the large reduction of beam induced movement with the use of an objective aperture or a conductive support film. To help interpret the low-dose images, we can apply slightly higher exposures to etch away the hydrophobic phase with the electron beam and reveal the network formed by the hydrophilic phase. Energy loss spectroscopy shows evidence that fluorine removal governs the beam damage process.

36 MATERIALS SCIENCE↗
NASA NTRS2007

Stochastic Effects in Computational Biology of Space Radiation Cancer Risk

Estimating risk from space radiation poses important questions on the radiobiology of protons and heavy ions. We are considering systems biology models to study radiation induced repair foci (RIRF) at low doses, in which less than one-track on average transverses the cell, and the subsequent DNA damage processing and signal transduction events. Computational approaches for describing protein regulatory networks coupled to DNA and oxidative damage sites include systems of differential equations, stochastic equations, and Monte-Carlo simulations. We review recent developments in the mathematical description of protein regulatory networks and possible approaches to radiation effects simulation. These include robustness, which states that regulatory networks maintain their functions against external and internal perturbations due to compensating properties of redundancy and molecular feedback controls, and modularity, which leads to general theorems for considering molecules that interact through a regulatory mechanism without exchange of matter leading to a block diagonal reduction of the connecting pathways. Identifying rate-limiting steps, robustness, and modularity in pathways perturbed by radiation damage are shown to be valid techniques for reducing large molecular systems to realistic computer simulations. Other techniques studied are the use of steady-state analysis, and the introduction of composite molecules or rate-constants to represent small collections of reactants. Applications of these techniques to describe spatial and temporal distributions of RIRF and cell populations following low dose irradiation are described.

Cucinotta, Francis A.↗
NASA NTRS2017

Navigating the Deployment and Downlink Tradespace for Earth Imaging Constellations

Distributed Spacecraft Missions (DSMs) are gaining momentum in their application to Earth Observation (EO) missions owing to their unique ability to increase observation sampling in spatial, spectral, angular and temporal dimensions simultaneously. DSM design includes a much larger number of variables than its monolithic counterpart, therefore, Model-Based Systems Engineering (MBSE) has been often used for preliminary mission concept designs, to understand the trade-offs and interdependencies among the variables. MBSE models are complex because the various objectives a DSM is expected to achieve are almost always conflicting, non-linear and rarely analytical. NASA Goddard Space Flight Center (GSFC) is developing a pre-Phase A tool called Tradespace Analysis Tool for Constellations (TAT-C) to initiate constellation mission design. The tool will allow users to explore the tradespace between various performance, cost and risk metrics (as a function of their science mission) and select Pareto optimal architectures that meet their requirements. This paper will describe the different types of constellations that TAT-C’s Tradespace Search Iterator is capable of enumerating (homogeneous Walker, heterogeneous Walker, precessing type, ad-hoc) and their impact on key performance metrics such as revisit statistics, time to global access and coverage. We will also discuss the ability to simulate phased deployment of the given constellations, as a function of launch availabilities and/or vehicle capability, and show the impact on performance. All performance metrics are calculated by the Data Reduction and Metric Computation module within TAT-C, which issues specific requests and processes results from the Orbit and Coverage module. Our TSI is also capable of generating tradespaces for downlinking imaging data from the constellation, based on permutations of available ground station networks - known (default) or customized (by the user). We will show the impact of changing ground station options for any given constellation, on data latency and required communication bandwidth, which in turn determines the responsiveness of the space system.

Nag, Sreeja↗
DOE OSTI2012

Hydrogen Infrastructure Market Readiness: Opportunities and Potential for Near-term Cost Reductions; Proceedings of the Hydrogen Infrastructure Market Readiness Workshop and Summary of Feedback Provided through the Hydrogen Station Cost Calculator

Recent progress with fuel cell electric vehicles (FCEVs) has focused attention on hydrogen infrastructure as a critical commercialization barrier. With major automakers focused on 2015 as a target timeframe for global FCEV commercialization, the window of opportunity is short for establishing a sufficient network of hydrogen stations to support large-volume vehicle deployments. This reportdescribes expert feedback on the market readiness of hydrogen infrastructure technology from two activities.

08 HYDROGEN↗