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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Energy-effective and low-cost carbon capture from point-sources enabled by water-lean solvents

Aqueous amines, as the most mature carbon capture technology, are subject to high energy and cost penalties due to the large water content in their formulations. Emerging technologies are in demand to enable a transition to a low-carbon global economy. However, rigorous process modeling and techno-economic analyses are limited for emerging carbon capture technologies. Here, four CO 2 -Binding Organic Liquids (CO 2 BOLs), all water-lean solvents were presented as promising options towards energy-effective and low-cost carbon capture from point sources. Rigorous solvent property and process models were developed in Aspen Plus for a coal-fired power plant with CO 2 BOL-based carbon capture unit. Techno-economic analyses were conducted in 2018 US pricing basis. The results suggest that water-lean formulations can minimize water condensation and vaporization, leading to a 36% energy saving compared with aqueous amines. Indeed, these CO 2 BOLs can capture up to 97–99% CO 2 from coal fired plant. The estimated carbon capture cost is about $40/tonne CO 2 at 90–97% carbon capture rate, about 12–23% less expensive than the conventional aqueous amine technology. The comparison between these CO 2 BOLs showed that in addition to vapor liquid equilibrium and kinetics (key properties for aqueous solvents), viscosity, volatility, and hydrophobicity, also have strong impacts on the performance of water-lean solvents. The methods presented in this work can be used to evaluate other emerging carbon capture technologies, while the results linking costs and performance of carbon capture solvents with their properties. Additionally, this work identifies research directions and targets for further reductions in total costs of capture from either cost or energy perspectives for these leading water-lean solvents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Influence of the Anionic Zinc-Adeninate Metal–Organic Framework Structure on the Luminescent Detection of Rare Earth Ions in Aqueous Streams

Rare earth elements (REEs) are critical to numerous technologies; however, a combination of increasing demand, environmental concerns, and monopolistic marketplace conditions has spurred interest in boosting the domestic REE production from sources such as coal utilization byproducts. The economic viability of this approach requires rapid, inexpensive, and sensitive analytical techniques capable of characterizing the REE content during resource exploration and downstream REE processing (e.g., analyzing REE separation, concentration, and purification production steps). Luminescence-based sensors are attractive because many REEs may be sensitized to produce element-specific emission. Hence, a single material may simultaneously detect and distinguish multiple REEs. Metal–organic frameworks (MOFs) can sensitize multiple REEs, but their viability has been hindered by sensitivity and selectivity challenges. Understanding how the MOF structure impacts the REE sensing efficacy is critical to the rational design of new sensors. Here, we evaluate the sensing performance of seven different anionic zinc-adeninate MOFs with different organic linkers and/or structures for the visible-emitting REEs Tb, Dy, Sm, and Eu. The choice of a linker determines which REEs are sensitized and significantly influences their sensitivity and selectivity against competing species (here, Fe(II) and HCl). For a given linker, structural changes to the MOF can further fine-tune the performance. The MOFs produce some of the lowest detection limits (sub-10 ppb for Tb) reported for the aqueous sensitization-based REE detection. Importantly, the most selective MOFs demonstrated the ability to sensitize the REE signal at sub-ppm levels in a REE-spiked acid mine drainage matrix, highlighting their potential for use in real-world sensing applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

On the advantages of exploiting memory in Markov state models for biomolecular dynamics

Biomolecular dynamics play an important role in numerous biological processes. Markov State Models (MSMs) provide a powerful approach to study these dynamic processes by predicting long time scale dynamics based on many short molecular dynamics (MD) simulations. In an MSM, protein dynamics are modeled as a kinetic process consisting of a series of Markovian transitions between different conformational states at discrete time intervals (called “lag time”). To achieve this, a master equation must be constructed with a sufficiently long lag time to allow interstate transitions to become truly Markovian. This imposes a major challenge for MSM studies of proteins since the lag time is bound by the length of relatively short MD simulations available to estimate the frequency of transitions. Here, we show how one can employ the generalized master equation formalism to obtain an exact description of protein conformational dynamics both at short and long time scales without the time resolution restrictions imposed by the MSM lag time. Using a simple kinetic model, alanine dipeptide, and WW domain, we demonstrate that it is possible to construct these quasi-Markov State Models (qMSMs) using MD simulations that are 5–10 times shorter than those required by MSMs. These qMSMs only contain a handful of metastable states and, thus, can greatly facilitate the interpretation of mechanisms associated with protein dynamics. A qMSM opens the door to the study of conformational changes of complex biomolecules where a Markovian model with a few states is often difficult to construct due to the limited length of available MD simulations.

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

Chemical Recycling of Polycaprolactones via Reactive Melt Processing

Chemical recycling is a promising technology for the deconstruction of waste plastics into monomers or other chemical intermediates, which can be converted into other value-added products or repolymerized into polymers. In this work, polycaprolactone and poly(4-propylcaprolactone) were chemically recycled by exploiting ring-closing depolymerization (RCD). To demonstrate the utility of this approach, reactive distillation experiments were initially conducted in a heated round-bottom flask with a distillation head to explore the effect of temperature and catalyst loading on RCD. Inspired by industrial devolatilization equipment, analogous experiments were conducted using a twin-screw melt compounder that was modified to simultaneously heat and mix polymer in the presence of a catalyst while continuously removing the evolved monomer vapors with a vacuum system and collecting them in a cold trap. Yield and selectivity of the recovered monomer were characterized by 1 H nuclear magnetic resonance spectroscopy and gas chromatography-mass spectrometry. Importantly, the more scalable twin-screw melt compounder approach produced values of monomer selectivity (∼90%) and yield (∼80%) similar to those of the round-bottom flask experiments. The recovered monomers were also successfully repolymerized into the same neat polymer with comparable molar masses without purification steps or adding initiator. Here, the results of this study promote the use of reactive devolatilization extrusion as a scalable approach to polyester depolymerization.

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

Stochastic machine learning via sigma profiles to build a digital chemical space

This work establishes a different paradigm on digital molecular spaces and their efficient navigation by exploiting sigma profiles. To do so, the remarkable capability of Gaussian processes (GPs), a type of stochastic machine learning model, to correlate and predict physicochemical properties from sigma profiles is demonstrated, outperforming state-of-the-art neural networks previously published. The amount of chemical information encoded in sigma profiles eases the learning burden of machine learning models, permitting the training of GPs on small datasets which, due to their negligible computational cost and ease of implementation, are ideal models to be combined with optimization tools such as gradient search or Bayesian optimization (BO). Gradient search is used to efficiently navigate the sigma profile digital space, quickly converging to local extrema of target physicochemical properties. While this requires the availability of pretrained GP models on existing datasets, such limitations are eliminated with the implementation of BO, which can find global extrema with a limited number of iterations. A remarkable example of this is that of BO toward boiling temperature optimization. Holding no knowledge of chemistry except for the sigma profile and boiling temperature of carbon monoxide (the worst possible initial guess), BO finds the global maximum of the available boiling temperature dataset (over 1,000 molecules encompassing more than 40 families of organic and inorganic compounds) in just 15 iterations (i.e., 15 property measurements), cementing sigma profiles as a powerful digital chemical space for molecular optimization and discovery, particularly when little to no experimental data is initially available.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Optimizing Multicomponent Distillation Configurations

Distillation is a ubiquitous process in the chemical and petrochemical industries to separate mixtures into their individual components and accounts for a large percentage of all separations in chemical and petrochemical plants. A large fraction of the separations are mixtures containing four or more components requiring multiple distillation columns that may not be optimized for energy efficiency. As a result, there are tens of thousands of suboptimal distillation columns in operation in the U.S. consuming approximately 2-3 Quads of energy per year. In addition, the equipment dedicated to separations contributes 40 – 70% of the capital and operating costs in a typical processing plant.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Computer Simulation of Complex Systems at the Extremes of pH (Final Report)

During the final funding period of the above-mentioned grant, a number of key milestones were achieved as they relate to the Separation Science program. Below are the descriptions of those efforts and the papers published in support of them (see also submitted publication list). There was a strong focus during the final funding period was on hydrated protons and the unique properties of acidic solutions, which as pertinent to many separations processes.

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

Harnessing Metal-Carbon Interactions to Obtain Enhanced Yield in Aromatics and Improved Coking Resistance in Methane Aromatization

Direct CH 4 conversion to value-added products in one step will transform the carbon-based world of fuel and energy, while valorizing an underutilized resource and reducing flared carbon into the atmosphere. Catalytic methane dehydroaromatization (MDA) directly converts CH 4 to value-added aromatic products such as benzene, light hydrocarbons and a significant amount of hydrogen, all of which are chemical commodities [6 CH 4 (g) → C 6 H 6 (g) + 9 H 2 (g)]. The remarkable feature of this reaction is that the formation of the first C-C bonds from CH 4 and oligomerization of the C 2 species occur in one direct step, thus lowering process costs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

A New Method to Overcome Carboxyamide Formation During AFEX Pretreatment of Lignocellulosic Biomass

Lignin-carbohydrate complexes (LCCs) in the plant cell wall are responsible for providing resistance against biomass-degrading enzymes produced by microorganisms. Four major types of lignin-carbohydrate bonds are reported in the literature, namely, benzyl ethers, benzyl esters, phenyl glycosides, and acetyl ester linkages. Ester’s linkages in the plant cell wall are labile to alkaline pretreatments, such as ammonia fiber expansion (AFEX), which uses liquid or gaseous ammonia to cleave those linkages in the plant cell wall and reduce biomass recalcitrance. Two competing reactions, notably hydrolysis and ammonolysis, take place during AFEX pretreatment process, producing different aliphatic and aromatic acids, as well as their amide counterparts. AFEX pretreated grasses and agricultural residues are known to increase conversion of biomass to sugars by four- to five-fold when subjected to commercial enzyme hydrolysis, yielding a sustainable feedstock for producing biofuels, biomaterials, and animal feed. Animal feed trials on dairy cows have demonstrated a 27% increase in milk production when compared to a control feedstock. However, the presence of carboxamides in feedstocks could promote neurotoxicity in animals if consumed beyond a certain concentration. Thus, there is the need to overcome regulatory hurdles associated with commercializing AFEX pretreated biomass as animal feed in the United States. This manuscript demonstrates a modified pretreatment for increasing the digestibility of industrial byproducts such as Brewer’s spent grains (BSG) and high-fiber meal (HFM) produced from BSG and dry distillers grains with soluble (DDGS), while avoiding the production of carboxamides. The three industrial byproducts were first treated with calculated amounts of alkali such as NaOH, Ca(OH) 2 , or KOH followed by AFEX pretreatment. We found that 4% alkali was able to de-esterify BSG and DDGS more efficiently than using 2% alkali at both 10 and 20% solids loading. AFEX pretreatment of de-esterified BSG, HFM, and DDGS produced twofold higher glucan conversion than respective untreated biomass. This new discovery can help overcome potential regulatory issues associated with the presence of carboxamides in ammonia-pretreated animal feeds and is expected to benefit several farmers around the world.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Gravitation and Mesh Adaption

The Gravitation and Mesh Adaptation (GaMA) toolbox consists of a set of Matlab classes for modeling the environment around asteroids and comets. A variety of gravitational models and supporting algorithms from are consolidated alongside a custom meshing utility tailored for the application. This allows the user to work within a single streamlined environment to import and manipulate surface definitions, probe the dynamical environment, integrate trajectories, and post-process results. For other applications, modified surface meshes can be exported. Gravity Models: 1) Werner's analytic polyhedron model 2) Mascon model 3) Gottlieb's spherical harmonic model 4) Approximate polyhedron models 5) Curvilinear surface models 6) Custom composite models Meshing Features: 1) Array-based half-edge data structure 2) Supports curvilinear surface definitions up to degree 4 3) Ray-tracing 4) Coarsening 5) Feature-based refinement 6) Projection 7) Smoothing 8) Mesh quality validity tests 9) Mesh repair Additional Features: 1) Solar radiation pressure model 2) Distant 3rd body model 3) Collision detection 4) Trajectory integration and post-processing 5) Visualization of surface fields

Pearl, Jason↗
DOE OSTI2021

Carbon dioxide capture with aqueous amino acids: Mechanistic study of amino acid regeneration by guanidine crystallization and process intensification

CO 2 capture from powerplant-generated flue gas via a phase-changing process involving absorption with aqueous amino acids (e.g., glycine or sarcosine) and bicarbonate crystallization with bis-iminoguanidines (e.g., glyoxal-bis-iminoguanidine or GBIG) is investigated in this paper. This process is of high interest due to its potential to decrease the energy penalty for CO 2 capture by significantly reducing the solvent regeneration energy typically associated with aqueous amine solvents. A critical step in the proposed CO 2 capture mechanism is the regeneration of the amino acid by removal of protons and bicarbonate ions from solution through crystallization of GBIGH 2 2+ bicarbonate salt. Here, we investigated the thermodynamics and kinetics of glycine regeneration by crystallization of GBIGH 2 2+ (HCO 3 – ) 2 (H 2 O) 2 . A theoretical model was developed and compared to experimental data to simulate and predict the glycine regeneration and determine its reaction mechanism. This combined experimental and theoretical study led to the conclusion that, while the GBIGH 2 2+ bicarbonate crystallization step provides most of the thermodynamic driving force for the glycine regeneration, the rate-limiting step is the protonation of GBIG prior to crystallization. The CO 2 loading and amino acid regeneration steps were combined into a single, intensified process using a bubble column reactor. The CO 2 loading capacity of GBIG was experimentally determined to be roughly 1.36 mol CO 2 per mol GBIG. These results provide the fundamental basis for developing an effective carbon capture technology with phase-changing amino acid/guanidine absorbents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

In situ feature analysis for large-scale multiphase flow simulations

The study of multiphase flow is essential for designing chemical reactors such as fluidized bed reactors (FBR), as a detailed understanding of hydrodynamics is critical for optimizing reactor performance and stability. An FBR allows scientists to conduct different types of chemical reactions involving multiphase materials, especially interaction between gas and solids. During such complex chemical processes, the formation of void regions in the reactor, generally termed as bubbles, is an important phenomenon. The study of these bubbles has a deep implication in predicting the reactor’s overall efficiency. But physical experiments needed to understand bubble dynamics are costly and non-trivial due to the technical difficulties involved and harsh working conditions of the reactors. Therefore, to study such chemical processes and bubble dynamics, a state-of-the-art computational simulation MFIX-Exa is being developed. Despite the proven accuracy of MFIX-Exa in modeling bubbling phenomena, the large-scale output data prohibits the use of traditional post hoc analysis capabilities in both storage and I/O time. Herein, to address these issues and allow the application scientists to explore the bubble dynamics in an efficient and timely manner, we have developed an end-to-end analytics pipeline that enables in situ detection of bubbles, followed by a flexible post hoc visual exploration methodology of bubble dynamics. The proposed method enables interactive analysis of bubbles, along with quantification of several bubble characteristics, enabling experts to understand the bubble interactions in detail. Positive feedback from the experts has indicated the efficacy of the proposed approach for exploring bubble dynamics in very-large-scale multiphase flow simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Robust Chemiresistive Behavior in Conductive Polymer/MOF Composites

Metal-organic frameworks (MOFs) are promising materials for gas sensing but are often limited to single-use detection. A hybridization strategy is demonstrated synergistically deploying conductive MOFs (cMOFs) and conductive polymers (cPs) as two complementary mixed ionic-electronic conductors in high-performing stand-alone chemiresistors. This work presents significant improvement in i) sensor recovery kinetics, ii) cycling stability, and iii) dynamic range at room temperature. The effect of hybridization across well-studied cMOFs is demonstrated based on 2,3,6,7,10,11-hexahydroxytriphenylene (HHTP) and 2,3,6,7,10,11-hexaiminotriphenylene (HITP) ligands with varied metal nodes (Co, Cu, Ni). A comprehensive mechanistic study is conducted to relate energy band alignments at the heterojunctions between the MOFs and the polymer with sensing thermodynamics and binding kinetics. The findings reveal that hole enrichment of the cMOF component upon hybridization leads to selective enhancement in desorption kinetics, enabling significantly improved sensor recovery at room temperature, and thus long-term response retention. This mechanism is further supported by density functional theory calculations on sorbate–analyte interactions. It is also found that alloying cPs and cMOFs enables facile thin film co-processing and device integration, potentially unlocking the use of these hybrid conductors in diverse electronic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Distributed sustainable metals production: opportunities for intensifying separations & alternative feedstocks

Meeting the increased demand for rare earth elements and beyond primary mined ore. Secondary sources like phosphogypsum, coal fly ash, used nuclear fuel, and electronic waste are concentrated sources of critical minerals. One strategy for a resilient supply chain is to decentralize sourcing and hydrometallurgical processing of metals. Rotating packed beds (RPBs) for solid-phase extraction and liquid-liquid extraction are gaining momentum for their ability to increase process throughput by 5-10x the state of the art. In conclusion, this review discusses advances in hydrometallurgical RPB processes and opportunities for implementation in distributed metals production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Cesium Removal Performance Comparisons of Crystalline Silicotitanate Media Batches with Savannah River Site Waste Simulant

The Tank Closure Cesium Removal (TCCR) system uses ion exchange columns filled with Crystalline Silicotitanate (CST) media to process radioactive waste solutions for the removal of Cs137. TCCR currently focuses on dissolving Savannah River Site (SRS) Tank 10H waste (primarily sodium salt cake solids) within the tank followed by at-tank ion exchange column treatment. Plans are underway to prepare and install a second TCCR unit at SRS. Capacity and particle size differences exist between archived (IE-911) and more recently-prepared CST media batches (9120- B and 9140-B). Side-by-side comparison testing was performed to evaluate the cesium removal performance of each batch to aid in selecting the preferred CST batch and media characteristics to load into the second TCCR unit. Batch contact equilibrium and flow-through column tests have been conducted with three CST batches using an SRS Average Simulant. Simulant batch contact equilibrium cesium loading results for the three CST batches (including two lots of one batch) are provided in Table ES-1. The 35 °C data indicates that the archived IE-911 batch has a higher cesium capacity than recently-prepared CST media and that the minor TCCR CST 9120-B media lot (2099000035) has similar cesium removal performance to the major TCCR lot (2099000034). Tests conducted at 25 ºC for the archived IE-911 CST batch indicated lower cesium removal performance with this simulant batch than was observed recently with a different SRS Average Simulant batch. A dilution factor (DF) is typically utilized when modeling engineered CST media cesium loading performance to account for mass contributions from the binder material. In cases where CST performance is lower than expected, this factor includes corrections for the binder and for low performance. The ZAM (Zheng, Anthony, and Miller) Isotherm Model DF values are provided in Table ES-1 for each simulant batch contact result. DF values near 0.5 were determined for the 9120-B and 9140-B CST batch contact tests while DF values near 0.6 (20% higher) were determined for the tests with IE-911. These dilution factors are lower than recently observed with a different SRS Average Simulant batch (9140-B DF = 0.68; IE-911 DF = 1.0). Based on these results, it appears that some component in the simulant solution used for equilibrium testing may have resulted in reduced cesium loading on the CST media.

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

Quantification of solution annealing effects on microstructure and property in a laser powder bed fusion 316H stainless steel

Solution annealing (SA) is an effective way to mitigate microstructural heterogeneity and to optimize mechanical performance of alloys manufactured by laser powder bed fusion (LPBF). In this study, a comprehensive and quantitative understanding of the recovery and recrystallization processes in the SA temperature range of LPBF 316H stainless steel is provided using results from analytical electron microscopy and in-situ high-energy synchrotron x-ray scattering. The profound effect of dislocation structures and secondary phase particles on mechanical performance, particularly under tension and creep conditions, is rationalized using deformation models that incorporate microstructural inputs. This study, for the first time, quantifies the broad effect of nano oxide inclusions on dislocation recovery kinetics, on grain growth and recrystallization kinetics, and on tension strength and creep resistance. The fundamental differences between the LPBF and the conventional wrought materials are revealed. The findings address critical questions in post-build processing of AM materials and pave the way for their rapid qualification for high temperature applications.

In-situ X-ray diffraction↗
DOE OSTI2025

Field Testing of Safeguards Technologies in the Hot Fuel Examination Facility

Recent developments in nuclear fuel reprocessing techniques have yielded more efficient processes and fuel cycle options that strengthen the nuclear industry and production of clean energy. One such area of interest is pyroprocessing of used oxide fuel. However, with these advances in the back end of the nuclear fuel cycle, advances in safeguards instrumentation, measurements, and approaches are needed to ensure special nuclear material (SNM) is accounted for according to regulatory requirements. As a high-level overview of a nominal pyroprocessing approach, used oxide fuel from commercial light water reactors (LWR) is mechanically removed from the metallic cladding. Then the fuel is crushed and randomized representative samples are taken and sent to an analytical lab for analysis. The analytical results of the feed material are used for input accountancy into the rest of the process. The crushed oxide fuel is then moved to the oxide reduction (OR) furnace where it is reduced from an oxide to metallic form. The OR product is distilled to remove salt and then moved to an electrorefiner (ER), where it is immersed in a eutectic mixture of lithium chloride potassium chloride (LiCl-KCl) that typically ranges between 450-550 ?. Within the ER, the usable uranium is electrochemically transported through the molten salt from the anode to the cathode, and then subsequently removed as a relatively pure U product.. A simplified model of pyroprocessing techniques with added emphasis on the safeguards can be seen below in Fig. 1

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗