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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A historical perspective on the regulation of cellulose biosynthesis

Cellulose is a β-1,4 linked glucose polymer that is synthesized by higher plants, algae and even by some bacteria and animals, making it the most abundant polymer on earth. As the major load bearing structure of the plant cell wall, it is hugely important in terms of plant growth and development, and in recent years it has gained interest for its biotechnological applications. Naturally, there has been a large concerted research effort to uncover the regulatory mechanisms underpinning cellulose synthesis. During the last century, several major breakthroughs in our understanding of cellulose synthesis in algae, bacteria, and plants have been pivotal in advancing the field of cellulose research, improving the likelihood that cellulose synthesis could be feasibly adapted for sustainable purposes. In this work, we will summarize the major hypotheses and advancements made during the last century on the regulation of cellulose biosynthesis, focusing on Arabidopsis thaliana.

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

Performance on HPC Platforms Is Possible Without C++

Computing at large scales has become extremely challenging due to increasing heterogeneity in both hardware and software. More and more scientific workflows must tackle a range of scales and use machine learning and AI intertwined with more traditional numerical modeling methods, placing more demands on computational platforms. These constraints indicate a need to fundamentally rethink the way computational science is done and the tools that are needed to enable these complex workflows. The current set of C++-based solutions may not suffice, and relying exclusively upon C++ may not be the best option, especially because several newer languages and boutique solutions offer more robust design features to tackle the challenges of heterogeneity. In June 2023, we held a mini symposium that explored the use of newer languages and heterogeneity solutions that are not tied to C++ and that offer options beyond template metaprogramming and Parallel. For for performance and portability. In conclusion, we describe some of the presentations and discussion from the mini symposium in this article.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Standardization of the Distributed Ledger Technology cybersecurity stack for power and energy applications

The global trend towards the integration of distributed energy resources is opening the doors to advanced, complex, and distributedmarketplaces. Such advanced ecosystems, where utility-owned and non utility-owned assets can contribute towards grid operations,generally require distributed communication and grid architectures, which can be supported by Distributed Ledger Technologies(DLTs). However, the potential of DLTs for long-term scalable solutions in operational technology applications has not been fullyutilized, partly due to the lack of standardization across and between different DLTs, as well as other supporting building blocks(e.g., communication protocols). This paper attempts to address this gap by proposing a DLT cybersecurity stack specificallydesigned for researchers, DLT technology developers, and end users (such as utilities). The DLT cybersecurity stack has beennotionally mapped to related cybersecurity components, namely: the Open Systems Interconnection (OSI) model, the TransmissionControl Protocol/Internet Protocol (TCP/IP) suite, and existing Smart Grid architecture frameworks. In addition, the paper discussesseveral cybersecurity implications, and demonstrates the potential uses of the DLT stack through multiple power and energy usecases. It is important to note that the stack can be also applied to the DLT use cases that are outside the power and energy domain.This work has been performed by the Cybersecurity Task Force under the IEEE P2418.5 Blockchain for Energy Standard workinggroup that is stationed under the IEEE Power and Energy Society’s Smart Buildings, Loads, and Customer Systems (SBLC)technical committee.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Multifidelity Monte Carlo estimation for efficient uncertainty quantification in climate-related modeling

Abstract. Uncertainties in an output of interest that depends on the solution of a complex system (e.g., of partial differential equations with random inputs) are often, if not nearly ubiquitously, determined in practice using Monte Carlo (MC) estimation. While simple to implement, MC estimation fails to provide reliable information about statistical quantities (such as the expected value of the output of interest) in application settings such as climate modeling, for which obtaining a single realization of the output of interest is a costly endeavor. Specifically, the dilemma encountered is that many samples of the output of interest have to be collected in order to obtain an MC estimator that has sufficient accuracy – so many, in fact, that the available computational budget is not large enough to effect the number of samples needed. To circumvent this dilemma, we consider using multifidelity Monte Carlo (MFMC) estimation which leverages the use of less costly and less accurate surrogate models (such as coarser grids, reduced-order models, simplified physics, and/or interpolants) to achieve, for the same computational budget, higher accuracy compared to that obtained by an MC estimator – or, looking at it another way, an MFMC estimator obtains the same accuracy as the MC estimator at lower computational cost. The key to the efficacy of MFMC estimation is the fact that most of the required computational budget is loaded onto the less costly surrogate models so that very few samples are taken of the more expensive model of interest. We first provide a more detailed discussion about the need to consider an alternative to MC estimation for uncertainty quantification. Subsequently, we present a review, in an abstract setting, of the MFMC approach along with its application to three climate-related benchmark problems as a proof-of-concept exercise.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Sensor enabled data-driven predictive analytics for modeling and control with high penetration of DERs in distribution systems

The electric power grid is undergoing a tremendous transformation due to the increasing penetration of renewable energy resources beginning with wind and more recently with the distributed energy resources (DERs) such as solar and battery storage. DERs have dramatically changed the role of the distribution systems in the overall power grid, and they are expected to contribute a significant portion of power generation in the future. If current trends for DERs continue, system operation and control will need to change dramatically for improved grid reliability and resiliency. As renewable resources increase in penetration, new and challenging operational, planning, and design problems are expected to emerge. Some of the key challenges that arise in the planning and operation of the future grid are: 1) Quantifying the impact of high DER penetration in distribution systems on bulk grid behavior over multiple time scales. 2) Identifying whether a particular DER configuration/settings have a large impact on the overall grid behavior. These challenges can be addressed in an offline manner using detailed T&D grid models and they can also be addressed in an online manner using sensor measurements. In particular, the advancement and planned growth in sensor technology in power grid over various voltage levels provide us with a unique opportunity to tackle these challenges from a data analytic perspective without needing detailed T&D grid models. A few questions that naturally arise when addressing the challenges from DERs using sensor data are: 1) How can we use limited sensor measurements to monitor & control voltage stability and small signal stability of the bulk system? 2) How can we ensure that the developed data analytic methods are robust to data availability and quality issues? 3) How can we compute the developed analytics in a scalable manner using streaming measurements? In this project, we addressed the aforementioned challenges arising from DERs and answered the questions raised above on how to effectively use the sensor measurements to enhance the reliability and performance of the electric grid. Thus, the overarching goal of this project is to develop effective reduced/representative system models from data that make the computational complexity sufficiently manageable so as to be useful to simulate, analyze, and even control complex non-linear power systems dynamics with large penetrations of DERs. In order to achieve the objective, the project team established a four-fold technical approach 1) Formulated a combined transmission-distribution co-simulation framework for data generation and validation, 2) Derived reduced/representative models of power systems based on data-driven methods for efficient computation and appropriate representation of system behavior, 3) Developed data driven characterization of power system behavior based on transfer operator theory, machine learning and optimization for model estimation, 4) Incorporated a scalable data management and processing architecture using distributed Kafka streaming applications that coordinate input data streams to the developed data analytics. The key accomplishments of the project are: 1) Development of a scalable multi-timescale T&D co-simulation framework (both for steady state and for dynamic co-simulation) using commercial solvers (PSSE and GridLAB-D). The steady-state T&D co-simulation interface is shared with our industry partner (PJM). 2) A structured reduced order dynamic model of distribution systems that can represent partial motor stalling along with a systematic procedure to derive the model parameters. 3) A PMU based online method to monitor, localize and mitigate fault-induced delayed voltage recovery using DER reactive support and load control in distribution systems. 4) Development of linear operator based robust methodologies for dynamic state estimation, uncertainty quantification, system identification and trajectory prediction for power system dynamics. 5) An adaptive damping control for utilizing wind energy resources to provide oscillation damping and system stability. 6) Implementation of Kafka-based framework for efficient processing of streaming data using Linux-based local virtual environment.

DER integration↗
DOE OSTI2022

Transformational Challenge Reactor – On the Application of Design for Additive Manufacturing (DfAM) Techniques to the Conception of Nuclear Core

Additive manufacturing (AM) technologies are radically changing the way objects are designed and manufactured. They allow building by deposition and solidification of material layer by layer, enabling the possibility to create simple and complex features alike, almost seamlessly. Generally, the design optimization process requires to define objectives, design variables and constraints. Additive manufacturing does not challenge this process per se but does allow designers to completely redefine the constraints space as the ones originating from fabrication can be considerably relaxed compared to more “traditional” manufacturing. Thus, design optimization becomes naturally far more responsive to the actual physics being solved and considerably less influenced by fabrication limitations, leading to dramatically different designs. To take advantage of these new opportunities, so-called Designing for Additive Manufacturing (DfAM) techniques are emerging. Development of design techniques specifically tailored for additive manufacturing is warranted because, considering AM, the design space is typically considerably larger than with traditional manufacturing. The ability to explore the design space efficiently is of paramount importance for designers. This study proposes to investigate and apply some of these DfAM techniques to the conception of nuclear core. The goal being to assess if these new methods can be applied to core design and if core design could benefits from additive manufacturing technologies. After a brief investigation on the pertinence of some DfAM techniques for core design, algorithms are proposed and a workflow is established to carry neutronics and steady-state thermal-hydraulics analyses. To diminish the work load, the workflow has been automated using python modules. These modules allow the rapid creation of input files, post-treatment of output files and visualization. To test the pertinence of the proposed workflow, three test cases have been investigated: a research and test reactor, a micro-reactor and a space propulsion reactor. These test cases offered a variety of objectives, constraints and operating conditions. It is observed that the proposed workflow is capable of converging quickly and efficiently to valid design solutions. It is then concluded that DfAM techniques can be applied to core design.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Modified Isotherm Modeling to Predict Cs Exchange with Crystalline Silicotitanate in Tank Waste Simulants

The U.S. Department of Energy is working to expedite processing of Hanford tank waste supernate at the Hanford Waste Treatment and Immobilization Plant. To support this goal, Washington River Protection Solutions is designing a Tank Side Cesium Removal (TSCR) system for suspended solids and cesium (Cs/ 137 Cs) removal from Hanford tank waste supernate. The ion exchange media selected for Cs removal at TSCR is crystalline silicotitanate (CST) that is manufactured in a nearly spherical form by Honeywell UOP LLC (UOP; Des Plaines, IL) as product IONSIV® R9140-B (Na form). The Zheng Anthony Miller (ZAM) isotherm model (Zheng et al. 1997) is a multicomponent ion exchange model used to predict the exchange of Group I metals onto CST. The ZAM isotherm has historically been used to predict Cs distribution values from Hanford and Savannah River Site (SRS) tank waste simulants. Figure S.1 summarizes model predictions from the ZAM isotherm that indicate poor prediction of Cs distribution values for simple and complex simulants with the engineered form of CST, IONSIV® R9140-B, and IONSIV® R9120-B where the solid line indicates a perfect fit by the model. The dotted lines indicate ±20% error. Batch contact testing with Hanford tank waste complex and simple simulants was used in conjunction with SRS simulants to experimentally determine Cs distribution values using a modification to the original isotherm model. The experimentally determined maximum Cs capacity for IONSIV® R9140-B CST in both the simple and complex matrices was found to be 0.53±0.3 mmoles Cs/g of CST. This value is not drastically different from the maximum Cs capacity of 0.58 mmoles Cs/g TAM-5 reported by Zheng et al. (1997). However, it is important to note that TAM-5 (commercially IONSIV® IE-910) is a powder. Hamm et al. (2002) determined that a dilution factor was needed to account for the Zr(OH)2 binder in the engineered form of CST. Hamm et al. determined that a dilution factor of 0.68 was appropriate to account for binder contribution and correct overprediction of Cs exchange on the engineered form of CST in ZAM calculations. This reduced the total capacity from 0.58 mmol/g with TAM-5 to 0.39 mmol/g for the engineered form of CST (Hamm et al. 2002). Despite substituting the experimentally determined maximum Cs capacity of 0.55 mmoles Cs/g for the literature-reported capacity of 0.39 mmoles Cs/g, it was determined that additional modifications to the model’s equilibrium rate constants were necessary in refining the isotherm model. The modified model overpredicted K+ uptake by the CST when compared to digested CST results described by Campbell et al. (2019). The modified model was further revised to omit three of the five K+ exchange equilibrium reactions described by ZAM to reduce the additional K+ loading seen by the model. Figure S.2 summarizes the revised model isotherm predictions plotted against measured Kd values.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Securing the Modern Grid: Federal Investments, Digitization, and Supply Chain Strategy

Across the United States (U.S.) grid expansion and modernization is underway, paving the way for accelerated load growth and intelligent resource management. Digitization of the grid is supported by several state and federal programs, providing support for utilities installing advanced metering infrastructure (AMI), AI-powered analytics systems, battery energy storage systems (BESS), and distributed energy resource management systems (DERMS) to transform the grid from a one-way power delivery system into an intelligent, responsive network that will enable faster load growth and power expansion of data centers for advanced artificial intelligence (AI) applications. The digital transformation of America's grid presents opportunity for increased efficiency and resiliency but also introduces new digital risks that require careful management. Digital equipment often contains several vulnerabilities such as unencrypted communication protocols, and persistent remote access capabilities that could be exploited to manipulate device settings, coordinate service disruptions, or inject false data into grid operations. These digital risks become particularly important as the grid must rapidly scale to support AI-driven data centers, which the administration has identified as essential for maintaining U.S. technological leadership and economic competitiveness. These vulnerabilities are compounded by supply chain realities: Chinese manufacturers currently produce 70-90% of essential grid components including inverters, batteries, and control systems, with the U.S. lacking domestic manufacturing capacity for critical assets like extra-high voltage transformers. Recent federal legislation has established Foreign Entity of Concern (FEOC) restrictions to address these risks, requiring projects to achieve escalating thresholds of non-FEOC content to receive tax credits while utilities work to expand sourcing channels for their supply chains and strengthen security measures. These restrictions arrive precisely when utilities face unprecedented electricity demand growth driven by the rapid growth in data centers, creating a considerable challenge: rapidly expanding infrastructure while navigating complex compliance requirements while lacking viable alternatives for many critical components. Idaho National Laboratory (INL) and its partners have developed practical approaches to help utilities navigate these intersecting challenges as they leverage federal investment to strengthen and grow the grid. These solutions include Cyber-Informed Engineering (CIE) principles that build resilience directly into systems, the Cirrus tool for secure cloud migration, and enhanced procurement guidance that embeds security requirements throughout equipment lifecycles. Federal initiatives, such as the Technical Assistance for Digital Assurance (TADA) project, provide direct support to utilities implementing these approaches while facilitating knowledge sharing across the industry. While these tools and frameworks cannot eliminate all risks inherent in foreign supply chain dependencies, they offer pragmatic pathways for strengthening security posture without sacrificing the deployment momentum essential to meeting surging electricity demand. Ultimately, securing America's digital energy infrastructure demands dedicated coordination across multiple fronts: building domestic supply chains, implementing robust digital assurance practices, and maintaining the aggressive modernization timeline necessary for reliability, resilience, and energy independence.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Extracellular vesicles in β cell biology: Role of lipids in vesicle biogenesis, cargo, and intercellular signaling

Background: Type 1 diabetes (T1D) is a complex autoimmune disorder whose pathogenesis involves an intricate interplay between ß cells of the pancreatic islet, other islet cells, and cells of the immune system. Direct intercellular communication within the islet occurs via cell surface proteins and indirect intercellular communication has traditionally been as occurring via secreted proteins (e.g., endocrine hormones and cytokines). However, recent literature suggests that extracellular vesicles (EVs) secreted by ß cells constitute an additional and biologically important mechanism for transmitting signals to adjacent ß cells or immune cells. Scope of Review: This review summarizes the general mechanisms of EV formation, with a particular focus on how lipids and lipid signaling pathways influence their formation and cargo. We review the implications of EV release from ß cells for T1D pathogenesis, how EVs and their cargo might be leveraged as biomarkers of the early events leading to T1D, and how EVs might be engineered as a therapeutic candidate to counter T1D outcomes. Major Conclusions: Islet ß cells have been viewed as initiators and propagators of the cellular circuit giving rise to autoimmunity in T1D. In this context, emerging literature suggests that EVs may represent a conduit for communication that holds more comprehensive messaging about the ß cells from which they arise. As the field of EV biology advances, it opens the possibility that intervening with EV formation and cargo loading could be a novel disease-modifying approach in T1D.

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

Multifunctional Catalysts for the Tandem Reactions of Oxygenates

Industrially-relevant catalytic reactions rarely consist of a simple sequence of elementary steps. Moreover, kinetic coupling of multiple reactions on a catalyst surface is highly desired for process intensification and improved energy efficiency for large scale chemical transformations. The shifting landscape of hydrocarbon chemical feedstocks in the US also motivates research on the selective conversion of more complex molecules. One desirable type of catalytic reaction is the reduction of carboxylic acids that are produced from biomass feedstocks to their corresponding alcohols. The proposed research explores the fundamental importance of hydrogen spillover on a multifunctional catalyst for carboxylic acid reduction with H 2 composed of metal particles coupled to metal oxide particles. Recent work has demonstrated the excellent performance of supported tungsten oxide clusters for carboxylic acid reduction, but only after they are promoted with a late transition metal such as palladium. Elucidating the active state of the catalyst and the associated reaction mechanism for acid reduction on that active state are the overall goals of the proposed project and successful completion will enable future design of efficient multifunctional catalysts. The critically important role of the metal promoter is hypothesized to be its ability to dissociate H2 and spillover atomic H to the support. Although hydrogen spillover is a well-recognized phenomenon in catalysis, its role in both catalyst activation and catalytic turnover are still unresolved. The study combined materials synthesis, characterization, reactivity testing, and molecular simulations, to explore the effect of hydrogen chemical potential on the formation of the active catalytic sites and on the steady state catalytic reduction of carboxylic acid. Varying the hydrogen chemical potential through modification of the gas conditions, support composition, and metal loading to modulated the structure and catalytic performance of the reducible metal oxide. Dual function catalysts containing supported Pd and WO x species co-located on a non-reducible carrier (silica) and a reducible carrier (titania) were synthesized and characterized by electron microscopy, temperature-programmed reduction, and chemisorption. Spectroscopic methods such as X-ray absorption and UV-vis were also used to evaluate the catalysts, which were used in the reduction of propionic acid to aldehyde and alcohol. Quantum chemical calculations, including ab initio phase diagrams provided molecular insights into the H spillover phenomenon.

09 BIOMASS FUELS↗
DOE OSTI2020

The energetics and dynamics of confinement in flexible frameworks and molecular confinement

Porous frameworks form the chemical and structural basis for critical technologies in separations, catalysis, nuclear waste containment and biomedical applications. Hundreds of zeolites and metal organic frameworks (MOFs) have been synthesized, and their ability to separate and store hydrogen, methane and carbon dioxide has been investigated both experimentally and theoretically. Nevertheless, a fundamental and systematic molecular-level understanding of the thermodynamic and structural factors governing the stability and guest-host interactions in these materials lags behind focused studies of specific systems. Because the guest molecules interact with each other and with the host framework, molecular confinement is a finely balanced and complex phenomenon. The ability of the guest molecules to bind and diffuse through the pores is determined by the nature of the host framework which, in turn, responds to the nature and concentration of guest molecules and to pressure and temperature. The work explores how framework flexibility, tailored by structure, composition, temperature and pressure, is a general phenomenon, similar in nature but variable in extent, in both zeolites and MOFs and is part of a free energy landscape in which framework-guest interactions, pressure, and temperature result in changes in framework geometry and, in some cases, phase transitions. These subtle and/or pronounced changes in lattice geometry, energetics, and dynamics can play a decisive role in confinement and in differentiating the binding of molecules of similar size. The free energy landscape created by these structural changes links polymorphism, amorphization, “breathing,” “gate opening” and confinement. Specifically, the generality of such behavior arises from commonalities in lattice dynamics and energetics of frameworks containing a combination of strong rigid bonds and weaker more flexible deformation modes. Identifying and describing these common and collective phenomena is the focus of the research on a selected group of zeolites and MOFs. Structural studies using X-ray and neutron diffraction explore the mechanical functionality of these important materials, specifically how framework materials respond to changes in temperature, pressure and guest loading. These structural studies are combined with calorimetric measurements, using techniques uniquely developed in the participating laboratories, of heats of formation, heat capacities and entropies, and guest-host interactions. The experimental thermodynamic studies are complemented by inelastic neutron scattering studies of the lattice dynamics related both to framework vibrations and to guest-host interactions. The report below summarizes the work done at UC Davis, which is complemented by work done at BYU (Woodfield) and Virginia Tech (Ross).

36 MATERIALS SCIENCE↗
DOE OSTI2022

The energetics and dynamics of confinement in flexible frameworks and molecular confinement

Porous frameworks form the chemical and structural basis for critical technologies in separations, catalysis, nuclear waste containment and biomedical applications. Hundreds of zeolites and metal organic frameworks (MOFs) have been synthesized, and their ability to separate and store hydrogen, methane and carbon dioxide has been investigated both experimentally and theoretically. Nevertheless, a fundamental and systematic molecular-level understanding of the thermodynamic and structural factors governing the stability and guest-host interactions in these materials lags behind focused studies of specific systems. Because the guest molecules interact with each other and with the host framework, molecular confinement is a finely balanced and complex phenomenon. The ability of the guest molecules to bind and diffuse through the pores is determined by the nature of the host framework which, in turn, responds to the nature and concentration of guest molecules and to pressure and temperature. The work explores how framework flexibility, tailored by structure, composition, temperature and pressure, is a general phenomenon, similar in nature but variable in extent, in both zeolites and MOFs and is part of a free energy landscape in which framework-guest interactions, pressure, and temperature result in changes in framework geometry and, in some cases, phase transitions. These subtle and/or pronounced changes in lattice geometry, energetics, and dynamics can play a decisive role in confinement and in differentiating the binding of molecules of similar size. The free energy landscape created by these structural changes links polymorphism, amorphization, “breathing,” “gate opening” and confinement. Specifically, the generality of such behavior arises from commonalities in lattice dynamics and energetics of frameworks containing a combination of strong rigid bonds and weaker more flexible deformation modes. Identifying and describing these common and collective phenomena is the focus of the research on a selected group of zeolites and MOFs. Structural studies using X-ray and neutron diffraction explore the mechanical functionality of these important materials, specifically how framework materials respond to changes in temperature, pressure and guest loading. These structural studies are combined with calorimetric measurements, using techniques uniquely developed in the participating laboratories, of heats of formation, heat capacities and entropies, and guest-host interactions. The experimental thermodynamic studies are complemented by inelastic neutron scattering studies of the lattice dynamics related both to framework vibrations and to guest-host interactions. This research was a collaboration between UC Davis (A. Navrotsky) BYU (B. Woodfield) and Virginia Tech (N. Ross).

36 MATERIALS SCIENCE↗
DOE OSTI2021

High-resolution hourly surrogate modeling framework for physics-based large-scale building stock modeling

Surrogate modeling can play a key role in reducing high computational burdens for large-scale physics-based modeling and uncertainty quantification. With the rapid development of large-scale building stock energy modeling, surrogate modeling has also begun to be widely applied in this field; however, most existing surrogate models lack hourly time resolution for regional-scale modeling, which is essential for understanding building demand profiles and grid impacts. Further, there is generally a lack of necessary data and feature engineering frameworks specific to building modeling for efficiently managing large datasets and complex computations. Furthermore, this paper proposes a modeling framework for large-scale (city-/region-scale), high-resolution, high-fidelity surrogate building stock energy models. Our developed framework consists of six modules: (1) building stock energy modeling (ComStock TM and ResStock TM ), (2) data engineering for large simulation data, (3) high performance computing workflow, (4) feature engineering, (5) machine learning model development, and (6) model performance evaluation. Two case studies apply the developed framework in both residential and commercial building stock analysis to demonstrate its computational efficiency and surrogate modeling accuracies. Results show that surrogate models, when efficiently trained using the HPC workflow module, reach a high level of modeling accuracy for two case studies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Solvent-Induced Selectivity of Isoprene From Bio-Derived Prenol

In this work we demonstrate the selective catalytic conversion of prenol, which is an allylic alcohol that can be prepared from renewable resources to isoprene. The catalyst is an inexpensive molybdenum complex (Molyvan L) designed and used as an additive for lubricants. Isoprene is generated under relatively mild reaction parameters at 130–150°C, for 2 h, under vapor pressure conditions that do not exceed 50 psi. Two cases were studied: one in which Molyvan L was dissolved in a base oil at 1% concentration (weight/weight) and then mixed with a solvent and prenol and the other in which neat Molyvan L was introduced in the reaction and the base oil was replaced with the solvent and prenol. We investigated the selectivity of the reaction using the following solvents in both cases: dodecane, dodecanol, isododecane, octane, blendstock for oxygenate blending (BOB3), a fuel surrogate, a polyalphaolefin (PAO4), and methoxy polyethylene glycol (methoxy PEG350). Although conversion of prenol was above 94% in all experiments, isoprene was formed with various degrees of efficiency alongside a prenol isomeric alcohol, diprenyl ether and mixed ether via intramolecular and intermolecular dehydration reactions. Dodecane appeared to have the highest level of selectivity initially in base oil so we studied the effect of various dodecane-like solvents on isoprene yield and product profile. Surprisingly, octane (similar to dodecane) and isododecane (branched alkane) generated insignificant amounts of byproducts, essentially providing the highly desired isoprene with a very high selectivity. Branching of the solvent does not appear to have an effect on selectivity. Another advantage of this catalyst is the low loadings required to effect the transformation; that is, 0.25% (weight/volume) in the cases using neat Molyvan L and 0.5% (weight/volume) in the cases using Molyvan L dissolved in the base oil. Provided that prenol can be produced in large scale from bioresources, this work would enable the sustainable production of isoprene, in good yield, and with very high selectivity.

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

Determining the Solubility Behavior of Kogarkoite in Simulated Nuclear Waste

Kogarkoite (Na 3 FSO 4 ) is a sparingly soluble fluoride–sulfate double salt that has been identified in high level nuclear waste sludge at the Hanford Site and, more recently, in sludge batch compilation samples at the Savannah River Site (SRS). Due to its complex dissolution behavior, which exhibits an inverse dependence on sodium ion activity, the presence of this mineral poses significant challenges to waste retrieval and processing. Incomplete dissolution during sludge washing can lead to the retention of fluoride and sulfate in the high-level waste feed, potentially causing the formation of corrosive, immiscible molten salt layers, known as "glass gall,” in vitrification melters. Current efforts to optimize flowsheet parameters and wash-water volumes are hindered by the absence of a commercially available, certified reference material, which prevents the accurate calibration of analytical methods and the verification of dissolution kinetics. To address this critical gap, this research focuses on the laboratory synthesis of pure Kogarkoite to serve as a standard for comprehensive solubility and washing performance testing. A coupled synthesis and simulant campaign was executed using an evaporative crystallization protocol designed to replicate the dynamic concentration effects observed in tank farm operations. Thirteen simulant matrices were prepared by dissolving systematically varied ratios of sodium fluoride (NaF) and sodium sulfate (Na 2 SO 4 ) in deionized water under three distinct caustic regimes: 0.0 g (control), 4.0 g (~1 M), and 12.0 g (~3 M) sodium hydroxide (NaOH). While thermodynamic equilibrium models suggest that high-caustic environments should favor the stability of the double salt7, results from this evaporative study at 25 0 C revealed a distinct kinetic divergence. Simulants with high hydroxide loading predominantly yielded large, blocky crystals of sodium sulfate decahydrate (Na 2 SO 4 .10H 2 O). Successful synthesis of pure Kogarkoite was achieved exclusively in specific NaOH-free compositional windows, where the precipitate manifested as fine, opaque granular aggregates. Ion chromatography (IC) analysis confirmed phase purity through the simultaneous stoichiometric depletion of both fluoride and sulfate from the supernatant. This successful synthesis establishes a reproducible route to generate bulk Kogarkoite, enabling the subsequent phase of quantitative dissolution testing using inhibited water to optimize sludge-batch assembly.

Sarker, Md Sharif [Florida International Univ. (FI↗
DOE OSTI2020

Evaluation of Nuclear Spent Fuel Disposal in Clay-Bearing Rock - Process Model Development and Experimental Studies

The DOE R&D program under the Spent Fuel Waste Science Technology (SFWST) campaign has made key progress in modeling and experimental approaches towards the characterization of chemical and physical phenomena that could impact the long-term safety assessment of heat-generating nuclear waste disposition in deep clay/shale/argillaceous rock. International collaboration activities such as heater tests and postmortem analysis of samples recovered from these have elucidated key information regarding changes in the engineered barrier system (EBS) material exposed to years of thermal loads. Chemical and structural analyses of sampled bentonite material from such tests has as well as experiments conducted on these are key to the characterization of thermal effects affecting bentonite clay barrier performance and the extent of sacrificial zones in the EBS during the thermal period. Thermal, hydrologic, and chemical data collected from heater tests and laboratory experiments has been used in the development, validation, and calibration of THMC simulators to model near-field coupled processes. This information leads to the development of simulation approaches (e.g., continuum vs. discrete) to tackle issues related to flow and transport at various scales of the host-rock and EBS design concept. Consideration of direct disposal of large capacity dual-purpose canisters (DPCs) as part of the back-end SNF waste disposition strategy has generated interest in improving our understanding of the effects of elevated temperatures on the EBS design. This is particularly important for backfilled repository concepts where temperature plays a key role in the EBS behavior and long-term performance. This report describes multiple R&D efforts on disposal in argillaceous geologic media through development and application of coupled THMC process models, experimental studies on clay/metal/cement barrier and host-rock (argillite) material interactions, molecular dynamic (MD) simulations of water transport during (swelling) clay dehydration, first-principles studies of metaschoepite (UO 2 corrosion product) stability, and advances in thermodynamic plus surface complexation database development. Drift-scale URL experiments provides key data for testing hydrological-chemical (HC) model involving strong couplings of fluid mixing and barrier material chemical interactions. The THM modeling focuses on heater test experiments in argillite rock and gas migration in bentonite as part of international collaboration activities at underground research laboratories (URLs). In addition, field testing at an URL involves in situ analysis of fault slip behavior and fault permeability. Pore-scale modeling of gas bubble migration is also being investigated within the gas migration modeling effort. Interaction experiments on bentonite samples from heater test under ambient and elevated temperatures permit the evaluation of ion exchange, phase stability, and mineral transformation changes that could impact clay swelling. Advances in the development, testing, and implementation of a spent nuclear fuel (SNF) degradation model coupled with canister corrosion focus on the effects of hydrogen gas generation and its integration with Geologic Disposal Safety Assessment (GDSA). GDSA integration activities includes evaluation of groundwater chemistries in shale formations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Understanding the Origin of Negative Temperature Dependence and Activity of N-Coordinated Cobalt Sites During Ethylene Dimerization

The on-demand production of short-chain linear alpha olefins (LAOs; C4-C8) via C2H4 dimerization and oligomerization is industrially attractive, prompting extensive research on designing active, selective, and stable catalysts for industrial use. Cobalt supported on ammoniated carbon (Co(NH3)x/C) catalysts have shown remarkable activity and selectivity in this process. However, critical aspects such as the active phase, active site structure, the role of the catalyst support, cobalt loading effects, and the inverse correlation of the reaction rate with temperature remain inadequately understood. This study systematically explores these factors using a combination of steady-state differential catalytic tests, in situ molecular characterization including diffuse reflectance UV-Vis (DR-UV-Vis), Infrared, and Raman spectroscopies, and ex situ X-ray diffraction (XRD) and high annular aberration-corrected dark field transmission electron microscopy (HAADF-STEM). Various supports (SiO2, Al2O3, NH4-ZSM-5, g-C3N4, and C) and cobalt loadings (1.0-3.0 Co nm-2) were studied to determine the optimal catalyst composition and identify the active phase and sites. Carbon-supported catalysts uniquely produce C4-8 LAOs during C2H4 dimerization, with site-time-yield remaining constant (~10-3 s-1) for 1.0-4.0 Co nm-2 at prolonged reaction times (24-48?h time-on-stream). At higher loadings of 6.0 Co nm-2, the formation of crystalline CoO and Co3O4 phases reduces catalytic activity and LAO selectivity. Our findings show that active catalysts lack crystalline cobalt oxides and instead feature dispersed Co2+ sites, tetra-coordinated to a mix of N/NH3 and O/H2O ligands, which catalyze C2H4 dimerization via the Cossee-Arlman mechanism, exhibiting 1st order dependence on C2H4 concentration. The observed inverse rate-temperature correlation is attributed to compensation effects (i.e., presence of Cremer-Constable relationship) linked to changes in adsorption enthalpic and entropic factors.

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DOE OSTI2022

Subcomponent Validation of Composite Joints for Marine Energy Structures

The Marine Energy Advanced Materials project addresses the barriers and uncertainties facing marine renewable energy developers in using composite materials for load-bearing structures. Sponsored by the U.S. Department of Energy's Water Power Technologies Office, the multiyear project comprises of collaborators from the National Renewable Energy Laboratory (NREL), Sandia National Laboratories, Pacific Northwest National Laboratory (PNNL), Montana State University (MSU), Florida Atlantic University (FAU), and industry stakeholders. As part of the Marine Energy Advanced Materials project, marine renewable energy industry surveys and assessments were conducted to identify key materials and knowledge gaps that hinder the adoption of composite materials in marine renewable energy structures. Specific knowledge gaps highlighted for composite materials were environmental effects, fatigue strengths, and bonded and bolted interconnects (composite/composite and composite/metal). It was concluded that many of these gaps could be addressed through subcomponent validation; consequently, a program was developed at NREL with the goals of developing subcomponent validation methods for appropriate marine energy materials, which would improve the understanding of design allowables for full-scale structural components and joints. Ultimately, the aim is to reduce timelines and costs associated with full-scale structural validation efforts while also providing near-net-scale static and fatigue data of composite/metal subcomponents for marine renewable energy systems. To approach these goals, a testing program was developed at NREL to investigate a variety of materials and structural design details at the subcomponent scale to understand (a) the effects of harsh and corrosive marine energy environments and (b) the static and fatigue strengths of the complex geometries. The recent study from this testing program is perhaps the largest that has ever been conducted with respect to specimen scale and geographic diversity of underwater environmental conditions that the specimens were subjected to. A variety of specimen geometries were designed by NREL to highlight key features of multimaterial (composite/composite or metal/composite) interconnects that may be used in marine renewable energy structural designs. The designs used several different composite matrices, adhesives, and marine-grade steels, which were highlighted in the surveys as being the most appropriate for harsh marine environments. Composite panels were then manufactured at MSU, and were subsequently manufactured into test specimens by NREL. The specimens were shipped to FAU and PNNL for conditioning in ocean water tanks at various temperatures for an extended period. The specimens were then returned to NREL for structural validation. This presentation will provide an overview of recent advances within the testing program in terms of specimen design and test methods, and will discuss results and key findings of the subcomponent testing program to date at NREL.

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