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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 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Solid–Adsorbed Polymer–Electrolyte Interphases for Stabilizing Metal Anodes in Aqueous Zn and Non–Aqueous Li Batteries

Polymers are known to adsorb spontaneously from liquid solutions in contact with high-energy substrates to form configurationally complex, but robust phases that often exhibit higher durability than might be expected from the individual physical bonds formed with the substrate. Rational control of the physical, chemical, and transport properties of such interphases has emerged as a fundamental opportunity for scientific and technological advances in energy storage technology but requires in-depth understanding of the conformation states and electrochemical effect of the adsorbed polymers. Here, we analyze the interfacial adsorption of oligomeric polyethylene glycol (PEG) chains of moderate sizes dissolved in protic and aprotic liquid electrolytes and find that there is an optimum polymer molecular weight of approximately 400 Da at which the highest columbic efficiency is achieved for both Zn and Li deposition. Furthermore, these findings point to a simple, versatile approach for extending the lifetime of batteries.

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

Prebiotic Membranes and Micelles Do Not Inhibit Peptide Formation During Dehydration

Abstract Cycles of dehydration and rehydration could have enabled formation of peptides and RNA in otherwise unfavorable conditions on the early Earth. Development of the first protocells would have hinged upon colocalization of these biopolymers with fatty acid membranes. Using atomic force microscopy, we find that a prebiotic fatty acid (decanoic acid) forms stacks of membranes after dehydration. Using LC‐MS‐MS (liquid chromatography‐tandem mass spectrometry) with isotope internal standards, we measure the rate of formation of serine dipeptides. We find that dipeptides form during dehydration at moderate temperatures (55 °C) at least as fast in the presence of decanoic acid membranes as in the absence of membranes. Our results are consistent with the hypothesis that protocells could have formed within evaporating environments on the early Earth.

Cohen, Zachary R.↗
DOE OSTI2022

Single Atoms Anchored in Hexagonal Boron Nitride for Propane Dehydrogenation from First Principles

We report single-atom catalysts embedded in N-doped graphene have attracted great interest recently, but the hexagonal boron nitride (h-BN) is much less explored as a support. Using first principles density function theory and molecular dynamics, here we investigate the stability of Pt, Au, and Ru single atoms anchored at B and N vacancies on h-BN. We find that Pt and Ru single atoms are much more stable than Au on h-BN. We further examine propane dehydrogenation on these single-atom catalysts and find that Pt 1 at the B vacancy in h-BN and Ru 1 at the N vacancy in h-BN show excellent activity for propane dehydrogenation, as evidenced by low energy barriers for both dehydrogenation steps. Our work suggests that Pt and Ru single atoms anchored at vacancy sites in h-BN could be promising for propane dehydrogenation.

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

Crystallography Reveals Metal‐Triggered Restructuring of β‐Hairpins

Abstract Metal binding to β‐sheets occurs in many metalloproteins and is also implicated in the pathology of Alzheimer's disease. De novo designed metallo‐β‐sheets have been pursued as models and mimics of these proteins. However, no crystal structures of canonical β‐sheet metallopeptides have yet been obtained, in stark contrast to many examples for ɑ‐helical metallopeptides, leading to a poor understanding for their chemistry. To address this, we have engineered tryptophan zippers, stable 12‐residue β‐sheet peptides, to bind Cu(II) ions and obtained crystal structures through single crystal X‐ray diffraction (SC‐XRD). We find that metal binding triggers several unexpected supramolecular assemblies that demonstrate the range of higher‐order structures available to metallo‐β‐sheets. Overall, these findings underscore the importance of crystallography in elucidating the rich structural landscape of metallo‐β‐sheet peptides.

Thuc Dang, Viet↗
DOE OSTI2024

Distinct cellular expression and subcellular localization of Kv2 voltage‐gated K + channel subtypes in dorsal root ganglion neurons conserved between mice and humans

Abstract The distinct organization of Kv2 voltage‐gated potassium channels on and near the cell body of brain neurons enables their regulation of action potentials and specialized membrane contact sites. Somatosensory neurons have a pseudounipolar morphology and transmit action potentials from peripheral nerve endings through axons that bifurcate to the spinal cord and the cell body within ganglia including the dorsal root ganglia (DRG). Kv2 channels regulate action potentials in somatosensory neurons, yet little is known about where Kv2 channels are located. Here, we define the cellular and subcellular localization of the Kv2 paralogs, Kv2.1 and Kv2.2, in DRG somatosensory neurons with a panel of antibodies, cell markers, and genetically modified mice. We find that relative to spinal cord neurons, DRG neurons have similar levels of detectable Kv2.1 and higher levels of Kv2.2. In older mice, detectable Kv2.2 remains similar, while detectable Kv2.1 decreases. Both Kv2 subtypes adopt clustered subcellular patterns that are distinct from central neurons. Most DRG neurons co‐express Kv2.1 and Kv2.2, although neuron subpopulations show preferential expression of Kv2.1 or Kv2.2. We find that Kv2 protein expression and subcellular localization are similar between mouse and human DRG neurons. We conclude that the organization of both Kv2 channels is consistent with physiological roles in the somata and stem axons of DRG neurons. The general prevalence of Kv2.2 in DRG as compared to central neurons and the enrichment of Kv2.2 relative to detectable Kv2.1 in older mice, proprioceptors, and axons suggest more widespread roles for Kv2.2 in DRG neurons.

Neurosciences & Neurology↗
DOE OSTI2023

Probing the Behavior of Composition‐Tunable Ultrathin PtNi Nanowires for CO Oxidation and Small‐Molecule Electrocatalytic Reactions

We have successfully synthesized ultrathin nanowires of pure Pt, Pt 99 Ni 1 , Pt 9 Ni 1 , and Pt 7 Ni 3 using a modified room-temperature soft-template method. Analysis of both methanol oxidation reaction (MOR) and ethanol oxidation reaction (EOR) results found that the Pt 7 Ni 3 samples yielded the best performance with specific activities of 0.36 and 0.34 mA/cm 2 respectively. Additionally, formic acid oxidation reaction (FAOR) tests noted that both Pt and PtNi nanowires oxidize small organic molecules (SOMs) via an indirect pathway. CO oxidation data suggests little measurable performance without any pre-reduction treatment; however, after annealing in H 2 , we detected significantly improved CO 2 formation for both Pt 9 Ni 1 and Pt 7 Ni 3 motifs. These observations highlight the importance of pre-treating these nanowires under a reducing atmosphere to enhance their performance for CO oxidation. To explain these findings, we collected extended x-ray adsorption fine structure (EXAFS) spectroscopy data, consistent with the presence of partial alloying with a tendency for Pt and Ni to segregate, thereby implying the formation of a Pt-rich shell coupled with a Ni-rich core. Here, we also observed that the degree of alloying within the nanowires increased after annealing in a reducing atmosphere, a finding deduced through analysis of the coordination numbers and calculations of Cowley's short range order parameters.

36 MATERIALS SCIENCE↗
DOE OSTI2024

17 O NMR Spectroscopy Reveals CO 2 Speciation and Dynamics in Hydroxide-Based Carbon Capture Materials

Carbon dioxide capture technologies are set to play a vital role in mitigating the current climate crisis. Solid-state 17 O NMR spectroscopy can provide key mechanistic insights that are crucial to effective sorbent development. In this work, we present the fundamental aspects and complexities for the study of hydroxide-based CO 2 capture systems by 17 O NMR. We perform static density functional theory (DFT) NMR calculations to assign peaks for general hydroxide CO 2 capture products, finding that 17 O NMR can readily distinguish bicarbonate, carbonate and water species. However, in application to CO 2 binding in two test case hydroxide-functionalised metal-organic frameworks (MOFs) – MFU-4l and KHCO 3 -cyclodextrin-MOF, we find that a dynamic treatment is necessary to obtain agreement between computational and experimental spectra. We therefore introduce a workflow that leverages machine-learning force fields to capture dynamics across multiple chemical exchange regimes, providing a significant improvement on static DFT predictions. In MFU-4l, we parameterise a two-component dynamic motion of the bicarbonate motif involving a rapid carbonyl seesaw motion and intermediate hydroxyl proton hopping. For KHCO 3 -CD-MOF, we combined experimental and modelling approaches to propose a new mixed carbonate-bicarbonate binding mechanism and thus, we open new avenues for the study and modelling of hydroxide-based CO 2 capture materials by 17 O NMR.

NMR spectroscopy↗
DOE OSTI2024

Predictive analytics of selections of russet potatoes

We explore the application of machine learning algorithms specifically to enhance the selection process of Russet potato (Solanum tuberosum L.) clones in breeding trials by predicting their suitability for advancement. This study addresses the challenge of efficiently identifying high-yield, disease-resistant, and climate-resilient potato varieties that meet processing industry standards. Leveraging manually collected data from trials in the state of Oregon, we investigate the potential of a wide variety of state-of-the-art binary classification models. The dataset includes 1086 clones, with data on 38 attributes recorded for each clone, focusing on yield, size, appearance, and frying characteristics, with several control varieties planted consistently across four Oregon regions from 2013 to 2021. We conduct a comprehensive analysis of the dataset that includes preprocessing, feature engineering, and imputation to address missing values. We focus on several key metrics such as accuracy, F1-score, and Matthews correlation coefficient (MCC) for model evaluation. The top-performing models, namely a feedforward neural network classifier (Neural Net), a histogram-based gradient boosting classifier (HGBC), and a support vector machine classifier (SVM), demonstrate consistent and significant results. To further validate our findings, we conducted a simulation study using the aims, data-generating mechanisms, estimands, methods, and performance measures (ADEMP) framework, simulating different data-generating scenarios to assess model robustness and performance through true positive, true negative, false positive, and false negative distributions, area under the receiver operating characteristic curve (AUC-ROC) and MCC. The simulation results highlight that non-linear models like SVM and HGBC consistently show higher AUC-ROC and MCC than logistic regression, thus outperforming the traditional linear model across various distributions, and emphasizing the importance of model selection and tuning in agricultural trials. Variable selection further enhances model performance and identifies influential features in predicting trial outcomes. The findings emphasize the potential of machine learning in streamlining the selection process for potato varieties, offering benefits such as increased efficiency, substantial cost savings, and judicious resource utilization. Our study contributes insights into precision agriculture and showcases the relevance of advanced technologies for informed decision-making in breeding programs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Molecular-Level Overhaul of y-Aminopropyl Aminosilicone/Triethylene Glycol Post-Combustion CO2-Capture Solvents

Capturing carbon dioxide (CO2) from post-combustion gas streams is an energy-intensive process that is required prior to either converting or sequestering CO2. There are a few commercial offerings of 1st and 2nd generation aqueous amine technologies, however the cost of capturing CO2 with these technologies remains high. To decrease costs of capture, researchers are designing efficient solvent systems with the goal of being drop-in replacements for 1st and 2nd generation infrastructure. One approach has seen the development of water-lean solvents that aim to increase efficiency by reducing the water content in solution. Water-lean solvents such as GE’s GAP/TEG are promising technologies, with potential to halve the parasitic load to a coal-fired power plant, only if the intrinsically high solution viscosities and hydrolysis of the siloxane moieties could be mitigated. We present here, an integrated multidisciplinary approach to overhaul the GAP/TEG solvent system at the molecular level to mitigate hydrolysis while also reducing viscosity. We present molecular-level insights into chemical speciation of CO2-containing ions, showing that co-solvents and diluents have a negligible effect on reducing viscosity and are not needed. This finding allowed for the design of singlecomponent siloxane-free diamine derivatives with site-specific incorporation of selective chemical moieties for direct placement and orientation of hydrogen bonding to reduce viscosity. Ultimately, we present new single-component diamine formulations less susceptible to hydrolysis that exhibit up to a 98% reduction in viscosity compared to the initial GAP/TEG formulation.

Cantu Cantu, David↗
DOE OSTI2024

Enhanced Carbon‐Carbon Coupling at Interfaces with Abrupt Coordination Number Changes

Abstract Cu‐catalyzed electrochemical CO 2 reduction reaction (CO 2 RR) produces multi‐carbon (C 2+ ) chemicals with considerable selectivities and activities, yet required high overpotentials impede its practical application. Here, we design interfaces with abrupt coordination number (CN) changes that greatly reduce the applied potential for achieving high C 2+ Faradaic efficiency (FE). Encouraged by the mechanistic finding that the coupling between *CO and *CO(H) is the most probable C−C bond formation path, we use Cu 2 O‐ and Cu‐phthalocyanine‐derived Cu (OD−Cu and PD−Cu) to build the interface. Using operando X‐ray absorption spectroscopy (XAS), we find that the Cu CN of OD−Cu is ~11, favoring CO* adsorption, while the PD−Cu has a COH*‐favorable CN of ~4. Operando Raman spectroscopy revealed that the interfaces with abrupt CN changes promote *OCCOH formation. As a result, the designed catalyst achieves a C 2+ FE of 85±2 % at 220 mA cm −2 in a zero‐gap CO 2 electrolyzer. An improvement of C 2+ FE by 3 times is confirmed at the low potential regime where the current density is 60–140 mA cm −2 , compared to bare OD−Cu. We report a 45‐h stable CO 2 RR operation at 220 mA cm −2 , producing a C 2+ product FE of ~80 %.

Chemistry↗
DOE OSTI2023

The homogeneous mixing of MgO and H 2 O at extreme conditions

Investigating water worlds presents a unique opportunity to understand the fundamental processes of planetary formation and evolution. One key aspect is characterizing the interactions between water and rock under the pressures and temperatures present within these worlds. Investigating the conditions for the homogeneous mixing of these materials is imperative to characterizing bulk properties and evolution of water-rich exoplanets. Here, in this study, we use density functional molecular dynamics simulations to study MgO-H 2 O mixtures at high pressure–temperature conditions where H 2 O occurs in solid, superionic, or liquid form. MgO, the representative rocky material, can be either solid or liquid. We start from 500 K at 120 GPa, increasing the temperature step by step up to 8000 K. By inspection, we determine the temperature at which MgO-HO homogeneously mix in our simulations. At 6000 K and 174 GPa is when we find the system to homogeneously mix. This heat-until-it-mixes approach provides us with an upper bound on the temperature for the mixing of MgO and H 2 O. We find that homogeneous mixing occurs at sufficiently low temperatures to be relevant for the collisional growth of a water-rich planet.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Using phenology to unravel differential soil water use and productivity in a semiarid savanna

Savannas are water-limited ecosystems characterized by two dominant plant types: trees and an understory primarily made up grass. Different phenology and root structures of these plant types complicate how savanna primary productivity responds to changes in water availability. We tested the hypothesis that productivity in savannas is controlled by the temporal and vertical distribution of soil water content (SWC) and differences in growing season length of understory and tree plant functional types. To quantify the relationship between tree, understory, and savanna-wide phenology and productivity, we used PhenoCam and satellite observations surrounding an eddy covariance tower at a semiarid savanna site in Arizona, USA. We distinguished between SWC across two different depth intervals (shallow, <0–30 cm and deep, >30–100 cm). We found that tree greenness increased with SWC at both depths, while understory greenness was only sensitive to the shallower SWC measurements. Onset of ecosystem dormancy, estimated from satellite observations close to the eddy covariance tower, explained more variability in annual gross primary productivity (GPP) than in other phenometrics. Higher SWC led to an extended growing season, caused by delayed dormancy in trees, but the understory showed no evidence of delayed dormancy in wetter periods. We infer that the timing of ecosystem scale dormancy, driven by trees, is important in understanding changes in a savanna's GPP. These findings highlight the important effects of rainfall during the winter. These findings suggest that savanna GPP is conditional on different responses to moisture availability in each of the dominant vegetation components.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Projecting Recent Advancements in Battery Technology to Next–Generation Electric Vehicles

Electric vehicles (EVs) have seen rapid growth in adoption over the last several years. Advancements to increase battery life and performance, policy shifts, and high charging rate are expected to further accelerate the development of next generation of EVs. Battery improvements continue to emerge, enabling increased driving range, total distance driven over the life of vehicles, and ability to charge at high rates. Herein, an analysis framework to provide insights into inclusive design metrics, such as specific energy of batteries, energy consumption of vehicles, and charging power infrastructure development, is developed. Various cell-level fast charge protocols to realistic battery designs to understand the infrastructure needs associated with achieving range replacement of 32.25 km min -1 (20 mi min -1 ) are also scaled. Additionally, by calculating scaled power and peak to average power ratio, it is found that there needs to be more distinct alignment between the research efforts focused at the cell level and what is being developed for EV charging infrastructure needs. Finally, impact of high direct current voltage architecture in next-generation EVs is discussed. The findings in this work provide an insight into recent advancements in battery technology to next-generation EVs.

20 mi/min↗
DOE OSTI2023

Optimal Strategies for Hybrid Battery‐Storage Systems Design

As stationary hybrid energy‐storage systems (HESS) for power systems applications have recently drawn interest due to their enhanced performance and decreasing cost, developing systematic approaches for HESS design while considering controls is gaining traction. Herein, a method is presented to optimally design hybrid battery storage by proposing a mathematical modeling framework, formulated as a mixed integer linear programming model. The optimization is capable of handling multiple subsystems of batteries, considering their economic and technological performance. Decisions involve sizing of the batteries, optimal temporal and strategic dispatch to end uses, and energy sources for charging each battery. The applicability of the model is tested on four case studies for three battery chemistries representing distinct objectives: high‐power, high‐energy, and second life. Compared to traditionally designed battery storage with a homogeneous battery, optimally designed hybrid systems can save 12%–26% of system costs, depending on the nature of the dispatch profile. Findings point to design preference toward the second life battery supplemented with some high‐power or high‐energy battery capacity, or both. With the utilized electricity price structure, customers can experience approximately 10%–35% reduction in their bills.

Koleva, Mariya↗
DOE OSTI2020

Discretization limits of lattice‐Boltzmann methods for studying immiscible two‐phase flow in porous media

Summary Digital images of porous media often include features approaching the image resolution length scale. The behavior of numerical methods at low resolution is therefore important even for well‐resolved systems. We study the behavior of the Shan‐Chen (SC) and Rothman‐Keller (RK) multicomponent lattice‐Boltzmann models in situations where the fluid‐fluid interfacial radius of curvature and/or the feature size of the medium approaches the discrete unit size of the computational grid. Various simple, small‐scale test geometries are considered, and a drainage test is also performed in a Bentheimer sandstone sample. We find that both RK and SC models show very high ultimate limits: in ideal conditions the models can simulate static fluid configuration with acceptable accuracy in tubes as small as three lattice units across for RK model (six lattice units for SC model) and with an interfacial radius of curvature of two lattice units for RK and SC models. However, the stability of the models is affected when operating in these extreme discrete limits: in certain circumstances the models exhibit behaviors ranging from loss of accuracy to numerical instability. We discuss the circumstances where these behaviors occur and the ramifications for larger‐scale fluid displacement simulations in porous media, along with strategies to mitigate the most severe effects. Overall we find that the RK model, with modern enhancements, exhibits fewer instabilities and is more suitable for systems of low fluid‐fluid miscibility. The shortcomings of the SC model seem to arise predominantly from the high, strongly pressure‐dependent miscibility of the two fluid components.

Li, Zhe↗
DOE OSTI2023

Developing a roadmap for carbon capture, and storage in Oklahoma by assessing the viability of stacked storage

Abstract The Intergovernmental Panel on Climate Change concludes that CO 2 capture and storage (CCS) is critical for climate‐stabilizing energy transitions. In CCS, captured CO 2 is sequestered in saline aquifers within sedimentary basins. The CO 2 storage capacity and the rate of injection are functions of the geology of the saline aquifer, which is uncertain. To minimize impacts of this uncertainty, CCS projects could include backup plans, such as co‐locating geologic CO 2 storage (GCS) sites with or near existing CO 2 ‐enhanced oil recovery (CO 2 ‐EOR) operations. These “stacked storage” projects could hedge against uncertainty in the saline formation performance because captured CO 2 could be injected into either location in the event of unexpected events (e.g., the injectivity decreases). Here, we investigate the possibility and ramifications of developing CCS networks in Oklahoma that are amendable to stacked storage. We find that stacked storage is possible in Oklahoma but the counties with the lowest‐cost saline storage resources do not have existing CO 2 ‐EOR operations. At the systems level, we find it is slightly more expensive (e.g., $1/tCO 2 to $5/tCO 2 ) to site GCS in counties with CO 2 ‐EOR projects. This increased expense is largely due to increased CO 2 transportation costs because hundreds of km of additional pipeline is required to capture CO 2 from the lowest‐cost sources. Overall, our results suggest that it is optimal to build more pipelines and avoid injecting CO 2 in some of the lowest‐cost saline storage resources, to enable capturing CO 2 from the least‐cost sources. © 2023 Society of Chemical Industry and John Wiley & Sons, Ltd.

42 ENGINEERING↗