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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Can section 45Q tax credit foster decarbonization? A case study of geologic carbon storage at Acid Gas Injection wells in the Permian Basin

Carbon capture, utilization, and storage (CCUS) is an important pathway for meeting climate mitigation goals. While the economic viability of CCUS is well understood, previous studies do not evaluate the economic feasibility of carbon capture and storage (CCS) in the Permian Basin specifically regarding the new Section 45Q tax credits. We developed a technoeconomic analysis method, evaluated the economic feasibility of CCS at the acid gas injection (AGI) wells, and assessed the implication of Section 45Q tax credits for CCS at the AGIs. We find that the compressors, well depth, and the permit and monitoring costs drive the facility costs. Compressors are the predominant contributors to capital and operating expenditure driving the levelized cost of CO 2 storage. Strategic cost reduction measures identified include 1) sourcing of low-cost electricity and 2) optimizing operational efficiency in well operations. In evaluating the impact of the tax credits on CCS projects, facility scale proved decisive. We found that facilities with an annual injection rate exceeding 10,000 MT storage capacity demonstrate economic viability contingent upon the procurement of inputs at the least cost. The new construction of AGI wells were found to be economically viable at a storage capacity of 100,000 MT. The basin is heavily focused on CCUS (tax credit – $\$$65/MT CO 2 ), which overshadows CCS ($\$$85/MT CO 2 ) opportunities. Balancing the dual objectives of CCS and CCUS requires planning and coordination for optimal resource and pore space utilization to attain the basin's decarbonization potential. We also found that CCS on AGI is a lower cost CCS option as compared to CCS on other industries.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Assessing models of force-dependent unbinding rates via infrequent metadynamics

Protein–ligand interactions are crucial for a wide range of physiological processes. Many cellular functions result in these non-covalent “bonds” being mechanically strained, and this can be integral to proper cellular function. Broadly, two classes of force dependence have been observed—slip bonds, where the unbinding rate increases, and catch bonds, where the unbinding rate decreases. Despite much theoretical work, we cannot predict for which protein–ligand pairs, pulling coordinates, and forces a particular rate dependence will appear. Here, we assess the ability of MD simulations combined with enhanced sampling techniques to probe the force dependence of unbinding rates. We show that the infrequent metadynamics technique correctly produces both catch and slip bonding kinetics for model potentials. We then apply it to the well-studied case of a buckyball in a hydrophobic cavity, which appears to exhibit an ideal slip bond. Finally, we compute the force-dependent unbinding rate of biotin–streptavidin. Here, the complex nature of the unbinding process causes the infrequent metadynamics method to begin to break down due to the presence of unbinding intermediates, despite the use of a previously optimized sampling coordinate. Allowing for this limitation, a combination of kinetic and free energy computations predicts an overall slip bond for larger forces consistent with prior experimental results although there are substantial deviations at small forces that require further investigation. Furthermore, this work demonstrates the promise of predicting force-dependent unbinding rates using enhanced sampling MD techniques while also revealing the methodological barriers that must be overcome to tackle more complex targets in the future.

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

Atomically Dispersed Single Ni Site Catalysts for Nitrogen Reduction toward Electrochemical Ammonia Synthesis Using N 2 and H 2 O

Ammonia (NH 3 ) electrosynthesis gains significant attention as NH 3 is essentially important for fertilizer production and fuel utilization. However, electrochemical nitrogen reduction reaction (NRR) remains a great challenge because of low activity and poor selectivity. Herein, a new class of atomically dispersed Ni site electrocatalyst is reported, which exhibits the optimal NH 3 yield of 115 µg cm -2 h -1 at –0.8 V versus reversible hydrogen electrode (RHE) under neutral conditions. High faradic efficiency of 21 ± 1.9% is achieved at -0.2 V versus RHE under alkaline conditions, although the ammonia yield is lower. The Ni sites are stabilized with nitrogen, which is verified by advanced X-ray absorption spectroscopy and electron microscopy. Density functional theory calculations provide insightful understanding on the possible structure of active sites, relevant reaction pathways, and confirm that the Ni-N 3 sites are responsible for the experimentally observed activity and selectivity. Extensive controls strongly suggest that the atomically dispersed NiN 3 site-rich catalyst provides more intrinsically active sites than those in N-doped carbon, instead of possible environmental contamination. Overall, this work further indicates that single-metal site catalysts with optimal nitrogen coordination is very promising for NRR and indeed improves the scaling relationship of transition metals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

High-pressure synthesis and relationship between A-site ordering and local structure of multicomponent perovskites (Ln{sub 0.25}Mn{sub 0.75})(Al{sub 0.25}Ti{sub 0.75})O{sub 3}, Ln=La, Pr, Nd, Sm, Gd, Tb, Dy, Y

ABSTRACT: The synthesis of multicomponent perovskites (Ln{sub 0.25}Mn{sub 0.75})(Al{sub 0.25}Ti{sub 0.75})O{sub 3} (Ln=La, Pr, Nd, Sm, Gd, Tb, Dy, Y) have been investigated using a high-pressure and high-temperature (6 GPa, 1175 °C) technique. When Ln{sup 3+} is larger La{sup 3+}, Pr{sup 3+}, Nd{sup 3+}, the A-site ordered perovskites, LnMn{sub 3}(Al{sub 0.25}Ti{sub 0.75}){sub 4}O{sub 12} in Im-3, have been successfully synthesized. The A-site partially disordered one, (Sm{sub 0.80}Mn{sub 0.20})(Sm{sub 0.07}Mn{sub 0.93}){sub 3}(Al{sub 0.25}Ti{sub 0.75}){sub 4}O{sub 12} is also obtained. In the case of smaller Gd{sup 3+}, Tb{sup 3+}, Dy{sup 3+}, we have obtained no single phase but two decomposed perovskite phases. When Ln{sup 3+} is much smaller Y{sup 3+}, it is crystallized as an A-site disorder one in Pnma. The Rietveld structural refinements of the A-site ordered and partially disordered perovskites indicate that the tilting of (Al/Ti)O{sub 6} octahedrons for the A-site ions ordering is correlated with the (Al/Ti)–O and Ln–O bond lengths to optimize the coordination of the A- and A′-sites. The phase stability of the A-site ordered perovskites is discussed from the viewpoint of this correlation. - Graphical abstract: Ln{sup 3+} (VIII) ionic radius dependence of BO{sub 6} octahedron tilt angle and A/B–O distance of Im-3 perovskites (Ln{sub 0.25}Mn{sub 0.75})(Al{sub 0.25}Ti{sub 0.75})O{sub 3} (Ln=La-Sm).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Solid state reaction synthesis and photoluminescence properties of Dy{sup 3+} doped Ca{sub 3}Sc{sub 2}Si{sub 3}O{sub 12} phosphor

Highlights: • Ca{sub 3−x}Sc{sub 2}Si{sub 3}O{sub 12}:xDy{sup 3+} (0.01 ≤ x ≤ 0.03) was successfully synthesized under a reducing atmosphere. • The thermal stability of the Ca{sub 2.975}Sc{sub 2}Si{sub 3}O{sub 12}:0.025Dy{sup 3+} is superior to commercial phosphors in theory and experiment. • The optimal chromaticity coordinates of Ca{sub 3}Sc{sub 2}Si{sub 3}O{sub 12}:Dy{sup 3+} is (x = 0.3425, y = 0.3343) upon 350 nm excitation. - Abstract: The white emission phosphor Ca{sub 3}Sc{sub 2}Si{sub 3}O{sub 12}:Dy{sup 3+} was synthesized by the solid-state reaction. Phase analysis and characteristic luminescence properties are investigated by X-ray diffraction and photoluminescence spectra measurement. Ca{sub 3}Sc{sub 2}Si{sub 3}O{sub 12}:Dy{sup 3+} phosphor shows strong absorption in 350–410 nm region and exhibits white emission with CIE chromaticity coordinates of (0.3425, 0.3343). Its emission intensity at 250 °C remained 74% of that measured at room temperature. Moreover, the activation energy is also calculated through the Arrhenius equation. The result shows that the thermostability of Ca{sub 3}Sc{sub 2}Si{sub 3}O{sub 12}:Dy{sup 3+} is superior than that of commercial phosphor Ca{sub 3}Sc{sub 2}Si{sub 3}O{sub 12}:Ce{sup 3+}. The outstanding luminescent properties indicate that Ca{sub 3}Sc{sub 2}Si{sub 3}O{sub 12}:Dy{sup 3+} could be a potential white light emission phosphor.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Controlling Ion Coordination Structure and Diffusion Kinetics for Optimized Electrode-Electrolyte Interphases and High Performance Si Anodes

The cycling performance of batteries is largely determined by electrode-electrolyte interphase associated with the chemical and electrochemical properties of electrolyte salts and solvents. In this work, we used a localized high concentration electrolyte (LHCE) that enables high performance of Si anodes as a model system and investigated the scientific mechanism behind the optimization of electrolyte. The correlation between electrode (cathode/anode)-electrolyte interphase and ion coordination structure and diffusion kinetics were elucidated systematically. Among all the LHCEs tested, the one with 1.8M LiFSI concentration and 1:2 molar ratio of carbonate solvents and fluorinated diluents has the highest proportion of solvent-separated ion pairs and contact ion pairs and fastest ion diffusion. It enables the most stable electrode-electrolyte interphase and hence the best Si anode performance. These results reveal the fundamental mechanism behind the stability of LHCEs and provide guidance on the new electrolyte design for Si anodes and other battery systems.

Jia, Haiping↗
DOE OSTI2023

Machine Learning Models for Predicting Molecular UV–Vis Spectra with Quantum Mechanical Properties

Accurate understanding of Ultraviolet–visible (UV–Vis) spectra is critical for highthroughput design of compounds for drug discovery. Experimentally determining UV–Vis spectra can become expensive when dealing with a large quantity of novel molecules. This provides us an opportunity to drive computational advances in molecular property predictions using quantum mechanics and machine learning. In this work, we use both Quantum Mechanically (QM) predicted and measured UV–Vis spectra as input to modify four different machine learning architectures: UVvis-SchNet, UVvis- DTNN, UVvis-Transformer, and UVvis-MPNN. Here we find that the UVvis-MPNN model outperforms the other models when using optimized 3D coordinates and QM predicted spectra as input features. This model has the highest performance for predicting UVVisible spectra with a training RMSE of 0.06 and validation RMSE of 0.08.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Approaches for More Efficient Biological Conversion of Lignocellulosic Feedstocks to Biofuels and Bioproducts

The future bioeconomy promises drop-in or performance-advantaged biofuels and bioproducts derived from lignocellulosic biomass, substantial greenhouse gas emissions reductions in sectors with few or no alternatives, and increased domestic energy production in countries with sufficient biomass resources. Despite the slower than anticipated pace of commercializing next-generation biofuels, the research community continues to make dramatic improvements at every stage of production, from feedstock cultivation through conversion to final products. However, the interdisciplinary nature of bioenergy research, and the need for cross-coordination among biologists, chemists, agronomists, and engineers, make coordinating and optimizing these strategies challenging. This Perspective surveys recent advancements in bioenergy crop engineering, lignocellulosic biomass deconstruction and fractionation, catabolism of biomass-derived sugars and aromatics, and biological conversion to fuels and products. Here, we organize major research approaches into broad categories and comment on which strategies offer synergies or trade-offs in the context of four approaches to improving the economics and carbon-efficiency of advanced biofuels and bioproducts: (1) maximize sugar conversion to a single product, (2) utilize diverse carbon sources for producing a single product, (3) convert lignin to high-value products, and (4) fractionate the hydrolysate to derive maximum value from each component.

09 BIOMASS FUELS↗
DOE OSTI2024

The reaction mechanism of the Ideonella sakaiensis PETase enzyme

Abstract Polyethylene terephthalate (PET), the most abundantly produced polyester plastic, can be depolymerized by the Ideonella sakaiensis PETase enzyme. Based on multiple PETase crystal structures, the reaction has been proposed to proceed via a two-step serine hydrolase mechanism mediated by a serine-histidine-aspartate catalytic triad. To elucidate the multi-step PETase catalytic mechanism, we use transition path sampling and likelihood maximization to identify optimal reaction coordinates for the PETase enzyme. We predict that deacylation is likely rate-limiting, and the reaction coordinates for both steps include elements describing nucleophilic attack, ester bond cleavage, and the “moving-histidine” mechanism. We find that the flexibility of Trp185 promotes the reaction, providing an explanation for decreased activity observed in mutations that restrict Trp185 motion. Overall, this study uses unbiased computational approaches to reveal the detailed reaction mechanism necessary for further engineering of an important class of enzymes for plastics bioconversion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Projected metastable Markov processes and their estimation with observable operator models

The determination of kinetics of high-dimensional dynamical systems, such as macromolecules, polymers, or spin systems, is a difficult and generally unsolved problem — both in simulation, where the optimal reaction coordinate(s) are generally unknown and are difficult to compute, and in experimental measurements, where only specific coordinates are observable. Markov models, or Markov state models, are widely used but suffer from the fact that the dynamics on a coarsely discretized state spaced are no longer Markovian, even if the dynamics in the full phase space are. The recently proposed projected Markov models (PMMs) are a formulation that provides a description of the kinetics on a low-dimensional projection without making the Markovianity assumption. However, as yet no general way of estimating PMMs from data has been available. Here, we show that the observed dynamics of a PMM can be exactly described by an observable operator model (OOM) and derive a PMM estimator based on the OOM learning.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

The constrained architecture of mammalian Hox gene clusters

In many animal species with a bilateral symmetry, Hox genes are clustered either at one or at several genomic loci. This organization has a functional relevance, as the transcriptional control applied to each gene depends upon its relative position within the gene cluster. It was previously noted that vertebrate Hox clusters display a much higher level of genomic organization than their invertebrate counterparts. The former are always more compact than the latter, they are generally devoid of repeats and of interspersed genes, and all genes are transcribed by the same DNA strand, suggesting that particular factors constrained these clusters toward a tighter structure during the evolution of the vertebrate lineage. Here, we investigate the importance of uniform transcriptional orientation by engineering several alleles within the HoxD cluster, such as to invert one or several transcription units, with or without a neighboring CTCF site. We observe that the association between the tight structure of mammalian Hox clusters and their regulation makes inversions likely detrimental to the proper implementation of this complex genetic system. We propose that the consolidation of Hox clusters in vertebrates, including transcriptional polarity, evolved in conjunction with the emergence of global gene regulation via the flanking regulatory landscapes, to optimize a coordinated response of selected subsets of target genes in cis .

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Lanthanide binding peptide surfactants at air–aqueous interfaces for interfacial separation of rare earth elements

Rare earth elements (REEs) are critical materials to modern technologies. They are obtained by selective separation from mining feedstocks consisting of mixtures of their trivalent cation. We are developing an all-aqueous, bioinspired, interfacial separation using peptides as amphiphilic molecular extractants. Lanthanide binding tags (LBTs) are amphiphilic peptide sequences based on the EF-hand metal binding loops of calcium-binding proteins which complex selectively REEs. We study LBTs optimized for coordination to Tb 3+ using luminescence spectroscopy, surface tensiometry, X-ray reflectivity, and X-ray fluorescence near total reflection, and find that these LBTs capture Tb 3+ in bulk and adsorb the complex to the interface. Molecular dynamics show that the binding pocket remains intact upon adsorption. We find that, if the net negative charge on the peptide results in a negatively charged complex, excess cations are recruited to the interface by nonselective Coulombic interactions that compromise selective REE capture. If, however, the net negative charge on the peptide is −3, resulting in a neutral complex, a 1:1 surface ratio of cation to peptide is achieved. Surface adsorption of the neutral peptide complexes from an equimolar mixture of Tb 3+ and La 3+ demonstrates a switchable platform dictated by bulk and interfacial effects. The adsorption layer becomes enriched in the favored Tb 3+ when the bulk peptide is saturated, but selective to La 3+ for undersaturation due to a higher surface activity of the La 3+ complex.

Ortuno Macias, Luis E. (ORCID:0000000284342192)↗
DOE OSTI2025

Dynamic Boundary Microgrids Under Privatization Considerations

Microgrids have physical, electrical, and logical (data, network, and ownership) boundaries. To power unserved customer loads during an outage, microgrids can extend the traditional operational boundaries. This can become complex when considering microgrid-to-microgrid (M2M) interactions where sensitive information such as competitive microgrid operational data is not shared. This work proposes an optimization method coordinated between microgrid controllers and distribution management systems that limits data sharing. The method involves a competitive bidding strategy that maximizes unserved load coverage while minimizing resource utilization and sensitive operational data sharing among entities. The work is validated on a two-microgrid system with photovoltaic and energy storage systems and curves of load derived from real world residential buildings datasets. Results show that the proposed method, when applied for three distinct use cases of energy storage sufficiency to cover the predefined boundary and/or the expanded boundary, can successfully select and bid the available load coverage.

Starke, Michael [ORNL] (ORCID:0000000221211195)↗
DOE OSTI2022

An Efficient Power Flexibility Aggregation Framework via Coordinate Transformation and Chebyshev Centering Optimization

The large-scale integration of distributed energy resources (DERs) converts the role of a distribution system from a customer to a prosumer. In this context, the controllable DERs are expected to provide capacity support for the transmission system, which can be considered as power flexibility aggregation. Specifically, it is a process of controlling the power output of DERs to fulfill the desired capacity or flexibility. However, the power output of DERs as control variables is redundant. That is, a power flexibility command can be realized by multiple dispatch alternatives, which may hinder efficient design of control rules and flexibility evaluation schemes. Therefore, this paper introduces a conception of the artificial power flexibility controller to avoid the redundancy issue, which is a converted control variable after reconstructing the DER power region. Through this reconstruction, the DERs can be indirectly controlled by the proposed artificial power flexibility controller. In addition, a Chebyshev centering optimization model is developed to approximate the power flexibility region. At last, the proposed method is verified on an artificially-designed network with multiple DERs.

Chebyshev centering optimization↗
DOE OSTI2024

An Efficient Checkpointing System for Large Machine Learning Model Training

As machine learning models increase in size and complexity rapidly, the cost of checkpointing in ML training became a bottleneck in storage and performance (time). For example, the latest GPT-4 model has massive parameters at the scale of 1.76 trillion. It is highly time and storage consuming to frequently writes the model to checkpoints with more than 1 trillion floating point values to storage. This work aims to understand and attempt to mitigate this problem. First, we characterize the checkpointing interface in a collection of representative large machine learning/language models with respect to storage consumption and performance overhead. Second, we propose the two optimizations: i) A periodic cleaning strategy that periodically cleans up outdated checkpoints to reduce the storage burden; ii) A data staging optimization that coordinates checkpoints between local and shared file systems for performance improvement.

machine learning, artificial intelligence↗
DOE OSTI2016

TH-AB-207A-05: A Fully-Automated Pipeline for Generating CT Images Across a Range of Doses and Reconstruction Methods

Purpose: To evaluate the robustness of CAD or Quantitative Imaging methods, they should be tested on a variety of cases and under a variety of image acquisition and reconstruction conditions that represent the heterogeneity encountered in clinical practice. The purpose of this work was to develop a fully-automated pipeline for generating CT images that represent a wide range of dose and reconstruction conditions. Methods: The pipeline consists of three main modules: reduced-dose simulation, image reconstruction, and quantitative analysis. The first two modules of the pipeline can be operated in a completely automated fashion, using configuration files and running the modules in a batch queue. The input to the pipeline is raw projection CT data; this data is used to simulate different levels of dose reduction using a previously-published algorithm. Filtered-backprojection reconstructions are then performed using FreeCT-wFBP, a freely-available reconstruction software for helical CT. We also added support for an in-house, model-based iterative reconstruction algorithm using iterative coordinate-descent optimization, which may be run in tandem with the more conventional recon methods. The reduced-dose simulations and image reconstructions are controlled automatically by a single script, and they can be run in parallel on our research cluster. The pipeline was tested on phantom and lung screening datasets from a clinical scanner (Definition AS, Siemens Healthcare). Results: The images generated from our test datasets appeared to represent a realistic range of acquisition and reconstruction conditions that we would expect to find clinically. The time to generate images was approximately 30 minutes per dose/reconstruction combination on a hybrid CPU/GPU architecture. Conclusion: The automated research pipeline promises to be a useful tool for either training or evaluating performance of quantitative imaging software such as classifiers and CAD algorithms across the range of acquisition and reconstruction parameters present in the clinical environment. Funding support: NIH U01 CA181156; Disclosures (McNitt-Gray): Institutional research agreement, Siemens Healthcare; Past recipient, research grant support, Siemens Healthcare; Consultant, Toshiba America Medical Systems; Consultant, Samsung Electronics.

60 APPLIED LIFE SCIENCES↗