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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Protonation Dynamics of Confined Ethanol–Water Mixtures in H-ZSM-5 from Machine Learning-Driven Metadynamics

Zeolites are indispensable heterogeneous catalysts in industrial chemical processes, valued for their strong Brønsted acidity, well-defined microporous frameworks, and tunable pore structures. Their catalytic activity arises primarily from Brønsted acid sites (BAS), typically present as bridging hydroxyl groups (Si–OH–Al). Under aqueous reaction conditions, these protons interact dynamically with water and alcohol molecules, leading to complex solvation and protonation behavior within confined pores. In this study, we investigate the protonation equilibrium occurring between ethanol and water at the BAS of acidic zeolites under varying hydration levels, i.e., C2H5OH–(H2O)n, n=1–4. Local structure was analyzed through an adaptive-learning global optimization algorithm, while enhanced sampling molecular dynamics simulations with Well-Tempered Metadynamics (WMetaD) and machine learning interatomic potentials (MLPs) provide free-energy surfaces (FES) at variable hydration levels. The results reveal a strong dependence of proton localization on the degree of hydration. At low hydration (1 water molecule), the proton resides predominantly on ethanol; with 2 water molecules, it shifts toward water, and at higher hydration (3 or more water molecules), it becomes extensively delocalized over the water cluster. These findings underscore the critical role of solvation in modulating acid site behavior and suggest that a minimum of three water molecules is necessary to fully stabilize the proton on water within the zeolite framework. This solvation threshold has significant implications for catalytic processes, particularly in biomass conversion reactions where alcohol protonation is a key step in dehydration mechanisms.

machine learning↗
DOE OSTI2024

Investigation of Sub‐Bandgap Emission and Unexpected n‐Type Behavior in Undoped Polycrystalline CdSe x Te 1‐x

Abstract Se alloying has enabled significantly higher carrier lifetimes and photocurrents in CdTe solar cells, but these benefits can be highly dependent on CdSe x Te 1‐x processing. This work evaluates the optoelectronic, chemical, and electronic properties of thick (3 µm) undoped CdSe x Te 1‐x of uniform composition and varied processing conditions (CdSe x Te 1‐x evaporation rate, CdCl 2 anneal, Se content) chosen to reflect various standard device processing conditions. Sub‐bandgap defect emission is observed, which increased as Se content increased and with “GrV‐optimized CdCl 2 ” (i.e., CdCl 2 anneal conditions used for group‐V‐doped devices). Low carrier lifetime is found for GrV‐optimized CdCl 2 , slow CdSe x Te 1‐x deposition, and low‐Se films. Interestingly, all films (including CdTe control) exhibited n‐type behavior, where electron density increased with Se up to an estimated ≈10 17 cm −3 . This behavior appears to originate during the CdCl 2 anneal, possibly from Se diffusion leading to anion vacancy (e.g., V Se , V Te ) and Cl Te generation.

14 SOLAR ENERGY↗
DOE OSTI2025

Abstraction of Hydride from Alkanes and Dihydrogen by the Perfluorotrityl Cation

Abstract Lewis acids play a central role in a large variety of chemical transformations. The reactivity of the strongest Lewis acids is typically studied in the context of affinity towards hard bases, such as fluoride or oxygenous species. Carbocations can be viewed as soft Lewis acids, possessing significant affinity for softer bases, such as hydride. This work presents the ambient‐temperature isolation of salts of the perfluorotrityl cation ((C 6 F 5 ) 3 C + or F 15 Tr + ) in combination with halogenated carborane anions. The F 15 Tr + cation exhibits remarkable hydride affinity, illustrated by the observation of hydride abstraction from dihydrogen, and of the rapid abstraction of hydride from −CH 2 −groups in alkanes. Theoretical studies support the favorability of hydride abstraction from dihydrogen, and indicate that the hydride abstraction from alkanes proceeds via a concerted hydride transfer process that is sensitive to steric effects.

Leong, Derek W. [Department of Chemistry Texas A&a↗
DOE OSTI2025

Abstraction of Hydride from Alkanes and Dihydrogen by the Perfluorotrityl Cation

Abstract Lewis acids play a central role in a large variety of chemical transformations. The reactivity of the strongest Lewis acids is typically studied in the context of affinity towards hard bases, such as fluoride or oxygenous species. Carbocations can be viewed as soft Lewis acids, possessing significant affinity for softer bases, such as hydride. This work presents the ambient‐temperature isolation of salts of the perfluorotrityl cation ((C 6 F 5 ) 3 C + or F 15 Tr + ) in combination with halogenated carborane anions. The F 15 Tr + cation exhibits remarkable hydride affinity, illustrated by the observation of hydride abstraction from dihydrogen, and of the rapid abstraction of hydride from −CH 2 −groups in alkanes. Theoretical studies support the favorability of hydride abstraction from dihydrogen, and indicate that the hydride abstraction from alkanes proceeds via a concerted hydride transfer process that is sensitive to steric effects.

Leong, Derek W. [Department of Chemistry Texas A&a↗
DOE OSTI2026

Kinetic and modeling studies of the mechanism of the dehydrogenation of Mg(BH 4 ) 2 to Mg(B 3 H 8 ) 2

Since its discovery over 15 years ago, the reversible dehydrogenation of Mg(BH 4 ) 2 to Mg(B 3 H 8 ) 2 has remained one of the more intriguing hydrogen-cycling systems. While the mechanism of this reaction has been the subject of a good deal of speculation and computational studies, prior to this work it had not been probed through kinetic studies. Previous reports of the dehydrogenation of Mg(BH 4 ) 2 to Mg(B 3 H 8 ) 2 have not included kinetic studies. The present studies have shown that the dehydrogenation of Mg(BH 4 ) 2 to Mg(B 3 H 8 ) 2 is suppressed by hydrogen pressure indicating that the rate-limiting step in this process involves hydrogen elimination. Computational modeling of kinetic data obtained from monitoring the hydrogen elimination from Mg(BH 4 ) 2 to Mg(B 3 H 8 ) 2 under static vacuum over a range of temperatures supports that the dehydrogenation occurs through a reversible three-step process in which the elimination of hydrogen from the [B 3 H 10 ] − intermediate is rate limiting. A mechanism involving the low energy transfer of neighboring BH3 groups is proposed to account for the formation of [B 3 H 8 ] − at relatively low temperatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Paired Neural Network for Matching Experimental and Predicted Infrared Spectra

Here, we present a novel machine learning (ML)-based scoring technique for determining the similarity between experimental and predicted infrared (IR) spectra for identification purposes. IR spectroscopy is a powerful technique used to identify the molecular structure and composition of a sample by measuring the unique vibrational frequency pattern of the molecule’s functional groups. Molecular identifications are often made by comparing experimental and reference spectra. However, the limited number of reference spectra available in spectral libraries can confound the identification process. Alternative identification procedures rely on in silico techniques to simulate spectra for a wide range of molecules. However, scoring spectral similarity between an experimental query and computationally predicted reference remains a significant challenge. Our proposed ML-based scoring technique overcomes these barriers by accurately and efficiently determining spectral similarity.

Neural Network↗
DOE OSTI2025

Characterizing Hydrated Polymers via Dielectric Relaxation Spectroscopy: Connecting Relative Permittivity, State of Water, and Salt Transport Properties of Sulfonated Polysulfones

Sulfonated polysulfone is a promising membrane material for separation and energy generation processes that rely on membranes to control the rates of small-molecule (e.g., water and ions) transport. The interactions among water molecules, ions, and the sulfonate groups in these polymers play a key role in controlling these rates of transport, but much remains unknown about these fundamental interactions in sulfonated polymers. In this study, we used dielectric relaxation spectroscopy to characterize water molecule dynamics in sulfonated polysulfone and Nafion. We found that the charged sulfonate groups contribute to a restriction of water molecule dynamics (i.e., a reduction in the characteristic time scale of dipolar motions) in a manner that is governed by the concentration and nature (i.e., conjugate base strength) of the sulfonate group. Additionally, we develop strategies to use these data to aid in modeling ion transport in sulfonated polysulfone. These results may be useful to guide engineering strategies for polymeric membranes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Additive-Induced Morphology Change of Polymer Film Enables Enhanced Charge Mobility and Faster Organic Electrochemical Transistor Switching

Conjugated polymers (CPs) play an important role in organic electrochemical transistors (OECTs) for bioelectronics and related applications, where they serve as channel materials. Currently, most successful polymers for CPs are re-engineered from traditional CPs by replacing hydrophobic alkyl side chains with hydrophilic ethylene glycol or ionic groups. Frustratingly, the enhanced ion transport often compromises the charge mobility of the original CP. In this work, we present an additive-mediated method to construct a modified poly(3-hexylthiophene) (P3HT) film to enable efficient ion migration. The additive is designed with a cleavable diazo group that releases nitrogen and 2-methoxyethanol, a volatile compound, to alter the P3HT film morphology. OECTs based on the film exhibit improved response times. Interestingly, the process also enhances the crystallinity of P3HT, leading to higher hole mobility compared with pristine P3HT. This study proposes an in situ strategy to achieve the functionality of the OMIEC via morphological regulation, offering a promising route to simultaneously enhance both ion accessibility and charge mobility.

Organic polymers↗
DOE OSTI2025

Metal–Metal Bonding Influences Hydride Reactivity in [Sn–Rh] 3+ and [Sn–Ni] 2+ Bimetallics

Heavier group 14 metal hydrides serve as key intermediates in catalytic transformations, such as hydroboration. Regenerating such intermediates via a clean hydride source like dihydrogen could provide catalytic processes with a more economical alternative to, e.g., silanes and hydridoborane reagents. Herein, we report our efforts toward this goal using a [Sn–Rh] 3+ bimetallic system with the formal Rh I center acting as a potential dihydrogen activator. Targeting the introduction of a hydride ligand to the bimetallic core, our reactivity studies have revealed a preference for the hydride ligand to be bound to the Rh center, instead of the Sn center. Finally, examination of the electronic structures of these complexes via theoretical and experimental methods has revealed the electron acceptor nature of the Rh center within the bimetallic core and offers an explanation for the localization of the hydride between metal centers.

anions↗
DOE OSTI2026

Multidimensional scaling informed by F -statistic: Visualizing grouped microbiome data with inference

Multidimensional scaling (MDS) is a widely used dimensionality reduction technique in microbial ecology data analysis that captures the multivariate structure of the data while preserving pairwise distances between samples. While improvements in MDS have enhanced the ability to reveal group-specific data patterns, these MDS-based methods require prior assumptions for inference, limiting their application in general microbiome analysis. Here, in this study, we introduce a new MDS-based ordination method, “F-informed MDS,” which configures the data distribution based on the F-statistic, the ratio of dispersion between groups sharing common and different characteristics. Using semisynthetic datasets, we demonstrate that the proposed method is robust to hyperparameter selection while maintaining statistical significance throughout the ordination process. Various quality metrics for evaluating dimensionality reduction confirm that F-informed MDS is comparable to state-of-the-art methods in preserving both local and global data structures. Its application to a diatom-associated bacterial community suggests the role of this new method in interpreting the community’s response to the host. Our approach offers a well-founded refinement of MDS that aligns with statistical test results, which can be beneficial for broader multidimensional data analyses in microbiology and ecology. This new visualization tool can be incorporated into standard microbiome data analyses.

Biological and medical sciences↗
DOE OSTI2026

Advancing Porous Carbons: Understanding the Importance of Surface Chemistry for the Energy–Environment Nexus

This review intends, in a critical way, the comprehensive view of the importance of porous carbons surface chemistry for their applications in an energy− environment nexus. Surface chemistry is presented as a combination of functional heteroatom-containing groups, dopants, and structural defects. First, we briefly address carbon surface chemical environment and the methods of its modification and characterization, indicating their practical limitations. Then, the effects of surface chemistry on separation, catalysis, energy storage, sensing and microwave absorption are introduced. Besides a critical analysis of published findings on these topics, we also include our views on the advancement in the processes which rely on porous carbons surface chemistry, and identify strategic areas and directions that should deserve further attention. We focus on new findings and important original contributions to the field. Since the community of carbon researchers grows following the strategic application of these materials, the role of functional groups, dopants and structural defects in various cutting-edge applications is emphasized, showing the progress in the field and the evolution of findings. A clear determination of the effects of carbon surface is often a challenge since carbons porosity and the locations of specific bonds/sites/ defects in the carbon texture provide nanoconfinement effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Selectivity of tris complexation for Ni(II), Co(II), and Fe(II) and its effect on carbonate precipitation under alkaline conditions

Simultaneous critical element recovery and ex-situ carbon mineralization of low-grade ultramafic deposits have garnered increasing interest. Understanding the selectivity of metal complexing organic ligands for various divalent metals present in ultramafic rocks during carbonate mineralization is required to optimize this process. Here we evaluate 2-amino-2-(hydroxymethyl)-1,3-propanediol (i.e., Tris) as a model for bidentate ligands that bind divalent metals with both amine and alcohol groups in alkaline conditions (pH 8–10.5) at 25 °C and 80 °C in carbonate-buffered solutions. Protonated Tris forms a stronger complex with metal ions and is selective for trace metals with Ni(II) > Co(II) > Fe(II) during carbonate precipitation, with the rates decreasing but selectivity increasing at lower temperature and lower pH. At 25 °C, metastable amorphous hydrated carbonates form, regardless of the amount of Tris present or pH values. At 80 °C and pH 8, the Co and Fe carbonates that form are a mixture of rosasite-group minerals (Co 2 CO 3 (OH) 2 (H 2 O) and Fe 2 CO 3 (OH) 2 ) and pure carbonates (sphaerocobaltite: CoCO 3 and siderite: FeCO 3 ), with the latter more stabilized with increasing Tris concentration. In mixed metal solutions without Tris at 25 °C where Fe:Ni or Fe:Co is 2:1, Fe increases the rates of Ni or Co carbonate precipitation. However, with increasing Tris concentration the presence of Ni or Co inhibits Fe carbonate precipitation. At 80 °C without Tris, Ni or Co substitute into the iron chukanovite (Fe 2 CO 3 (OH) 2 ) lattice, increasing Ni or Co carbonate precipitation rates. Increasing Tris concentration only slightly inhibits Fe and Co precipitation, but slows Ni precipitation up to 10 times, with Fe progressively partitioning into more pure carbonate phases with distinct crystalline morphologies. These findings suggest bidentate amine-bearing ligands may be effective at Ni and Co recovery during carbon mineralization of Fe-bearing ultramafic deposits at relatively low temperatures and slightly alkaline pH.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Datum: A Scientific Metadata Catalog

The data catalog market is currently flooded with a myriad of different products, but none serve the scientific community well. There are cloud-native tools like Databricks, Snowflake,to on-premise solutions like Collibra and Datahub. The common failing of all these tools however, is their inability to serve the scientific data community directly. Most catalogs are targeted towards financial, health, or user data - not sensor or scientific domain data. They also prioritize integrations that often don’t exist or are just starting to be used in the scientific realm - all while ignoring common scientific tools and file types. Datum is a catalog which targets the scientific data directly, including the tools and networks in which those tools are used. We work with the producers and consumers of the data where they are, targeting cloud and on-premise with a focus on classified networks. Datum is an Erlang/Elixir application. Technical Features Note: The features listed below are still under development and may change, slightly, upon final delivery of the product. File Formats - Datum has the ability to read additional metadata and provides processing pipelines for the following file formats: Plain Text, PDF, LaTeX, HTML, Open Document Format (.odt), XML, CSV/TSV (and other standard delimiters), OpenDocument Database and Spreadsheets, Geo-Referenced TIFF, Common Data Format, HDF/HDF5, LabView TDMS, Excel, DeltaTables, Parquet, Apache Iceberg, Apache Hudi and many others. Metadata Collection - Scanners for the local and networked file systems and cloud storage providers. Network integration with common databases such as MSSQL and MySQL. User Plugin System - Users are able to provide either file processing, metadata extraction, or sampling plugins in the programming language of their choice. Authentication/Authorization -: OIDC integration, SCIM provisioning and EntraID integration out of the box. Full user and group management system with a “least privilege” operating mode. Governance - Customizable data governance platform; dictate and enforce required metadata, enforce data embargos, and enforce user agreements and NDAs before data access. Ability to create health checks on data, rejecting abandoned or poorly curated data and automatically removing it from the search index. Ability for users to submit corrections. Search - Semantic search is a first class citizen. No licenses to expensive, external software required. Integrated use of vectors and vector-based search allows for AI agent integration at all levels of operation. Metadata Model - Display and control data’s lineage and connections to other data and data directories. Data is modeled after a filesystem - an organization instantly recognizable and navigable by most any user. CLI and SDK - Ships with a Command Line Interface (CLI) tool and with a fully-featured Python SDK. This allows for rapid and programmatic use of Datum by every level of user. Minimal Infrastructure - Datum ships as a single executable file and can be run on any operating system and most CPU architectures. Datum has no reliance on external databases, search indexing tools, or other outside services - and it runs equally well on edge computing devices, cloud services, or in a clustered HPC environment.

darrington, john↗
DOE OSTI2024

Optimizing iodine adsorption in functionalized metal-organic frameworks via an unprecedented positional isomerism strategy

Porous metal–organic frameworks (MOFs) have emerged as highly promising adsorbents for capturing radioiodine, a predominant fission product released during nuclear fuel reprocessing. However, systematic investigations into the correlation between MOF structure and iodine uptake capacity remain scarce. Here, we present a novel approach to enhance the iodine adsorption capacity of MOFs by optimizing linker functionalization. Using ligand-functionalized thorium-based MOFs as a structural platform, we demonstrate that ortho-amino-substitution near the node of the dicarboxylate linker significantly increases iodine adsorption capacity compared to meta-amino-substitution, where the amino groups are directed away from the node. Specifically, ortho-substituted Th-UiO-68-3,3”-(NH 2 ) 2 exhibits higher iodine uptake capacities than the meta-substituted Th-UiO-68-2,2”-(NH 2 ) 2 via both vapor diffusion-based (2.042 vs. 1.087 g/g) and solution-based (0.841 vs. 0.784 g/g) processes. Notably, the I 2 vapor adsorption capacity (2.042 g/g) of Th-UiO-68-3,3”-(NH 2 ) 2 represents the second highest among all reported Th-MOFs. Pair distribution function (PDF) studies reveal that the superior iodine uptake performance of ortho-functionalized MOFs can be attributed to the reduced steric hindrance of the amino groups compared with the meta-substituted variants. Finally, this research highlights how positional isomerism and its subtle alterations can significantly influence host–guest interactions, extending beyond simple structural considerations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

A multifunctional technology platform for sorbent construction using polyacrylonitrile scaffolds

Polyacrylonitrile (PAN) is a synthetic polymer that shows high potential for use in a wide range of environmental remediation applications. PAN can be implemented in various ways within a batch or continuous process stream for use as a passive scaffold holding active gettering materials in place or where the PAN scaffold (e.g., beads, fiber mats, membranes) is functionalized with active chelating groups (e.g., amine, hydrazide, amidoximes, carboxyl). Application spaces covered in this review include remediation of heavy metals (e.g., Ag, As, Cd, Cr6+, Cu, Pb, Sb, and Se), high-dose fission products (e.g., 90Sr, 137Cs), radioiodine (i.e., 129I), noble gases (i.e., Xe, 85Kr), rare earths (e.g., Ce, Y), and actinides (e.g., Am, Pu, U). Methods for producing PAN composite sorbents are discussed. Options are also discussed for removing the PAN matrix following chemisorption of an active contaminant to minimize waste volumes requiring disposal.

polyacrylonitrile, composite sorbents, sulfides, a↗
DOE OSTI2025

Platinum–Ruthenium Alloys Are Not Bifunctional CO Electro-Oxidation Catalysts: A Kinetic Analysis

Electro-oxidation of CO is a common kinetic bottleneck in many types of fuel cells and organic electrosynthesis processes. Alloys of Pt and Ru are often used as anode catalysts, with high activity attributed to bifunctionality; this suggests that Ru preferentially activates water to form surface hydroxyl groups that can react with Pt-bound CO. However, rigorous kinetic measurements have not confirmed this assertion under steady-state electro-oxidation conditions. Here, CO electro-oxidation is analyzed using several commercial Pt/C and Pt 100-x Ru x /C nanoparticle catalysts in acidic and alkaline electrolytes. Kinetic observables including apparent transfer coefficients and reaction orders are measured and evaluated using a degree of rate control analysis. The kinetic observables for both Pt and PtRu alloys are most consistent with competitive adsorption and Langmuir–Hinshelwood coupling across a single site-type, rather than two distinct sites. Furthermore, the role of Ru in CO electro-oxidation is assigned to be a purely electronic effect.

Alcohols↗
DOE OSTI2025

Investigating Kinetic Mechanisms of Soot Formation in Plasma Pyrolysis of Methane via Active Learning (Final Technical Report)

Plasma pyrolysis of methane is an effective route for zero-carbon hydrogen production. Yet, soot generated from pyrolysis of hydrocarbons is detrimental to the climate and human health. There is ample experimental and theoretical evidence that suggests polycyclic aromatic hydrocarbons (PAHs) are the molecular precursors to soot particles. The reaction pathways of PAH formation are intricately dependent on a multitude of process parameters, whose kinetic mechanisms are not well-understood in plasma pyrolysis. This project aims to leverage advances in the kinetic modeling of soot formation in combustion, as well as in surrogate modeling and active learning, to systematically investigate the effects of process parameter on the kinetics of PAH formation in plasma pyrolysis of methane. To this end, we propose to use the PAH formation kinetics model developed by the PPPL/PU group based on the well-established ABF and HACA mechanisms, coupled with low-temperature plasma models. We will develop an active learning (AL) framework based on Bayesian optimization to systematically and data-efficiently explore the complex and multivariable parameter space of plasma pyrolysis in order to quantify the effects of plasma and feed parameters on the ABF and HACA kinetic pathways. AL is the branch of machine learning concerned with systematically querying samples from a system (experimental or computational) to train a data-driven model that maps design parameters to a performance criterion. We will use the data generated via AL to perform global sensitivity analysis, combined with uncertainty quantification, to elucidate the impact of different reaction pathways on minimizing formation of soot precursors. This study will result in an improved understanding of kinetics of PAH formation in plasma pyrolysis and can pave the way for more advanced mechanistic studies (e.g., soot nucleation mechanisms). Additionally, the findings will be useful for establishing practical strategies for increasing the pyrolysis efficiency and producing high-grade carbon for synthesis of nanomaterials.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Facilitating Data Collection of Maintenance Events to Populate the Hydrogen Component Reliability Database (HyCReD)

The Hydrogen Component Reliability Database (HyCReD) is a collaborative project between the National Renewable Energy Laboratory, the University of Maryland, and hydrogen stakeholders to improve safety and reliability for hydrogen facilities by implementing component reliability data taxonomies that support hydrogen infrastructure failure rate analysis. The project aims to quantify failure rates of hydrogen components through high-quality data collection and analysis on root causes and maintenance needed. HyCReD provides a common database for cataloging hydrogen component failures which exists for reliability research in many other mature industries [2]. The database fills a gap for the hydrogen community by providing a scientifically rigorous approach to quantitative risk assessment (QRA), prognostic health management (PHM), and reliability-centered maintenance (RCM) analysis. High level results will be aggregated and anonymized to protect company sensitive information; detailed results will be used to help address issues of hydrogen components. These advanced analytics will support accelerated deployment of hydrogen infrastructure by enabling better: design and safety of projects (safety codes and standards development), infrastructure reliability and cost (component failure rates, maintenance protocols), and component R&D needs (robust supply chain). A key to a successful HyCReD implementation is facilitating the ease of reporting and data quality in the database that can be used for analysis. Maintenance data was a previously identified gap in initial efforts to populate and validate the database taxonomies [3]. Collection of maintenance data will be instrumental in identifying failure modes and rates, identifying incipient component failures or reduced performance, cataloging best practices for maintenance routines and methods for prognostic health management, and quantifying the risk and effect of different failure modes. Several key priorities are identified for streamlined data collection to achieve quality and detailed failure data: Applicability, Ease of Use, Accessibility, and Information Security. The HyCReD team has now begun deployment of the database to several companies and groups that have signed non-disclosure agreements to facilitate the data collection of failures in industry hydrogen refueling station infrastructure. This paper will provide an update into the process of HyCReD deployment including the development of a coding guide for facility personnel to reference and ensure data quality and consistency from one station to another as well as implementation of contextually dependent data fields of system taxonomy and formatted entries to provide ease of use. The goal is to communicate the lessons learned from the roll-out to technicians and engineers in the field, and the addition of need for high level of security to protect all stakeholders.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗