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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Higher Ion Selectivity with Lower Energy Usage Promoted by Electro-osmotic Flow in the Transport through Conical Nanopores

The tradeoff between selectivity and throughput presents fundamental challenges to improve desalination and charge storage, salinity gradient-based energy harvesting, memory device/circuit development, and so forth. The well-known ion-current rectification and the recently resolved time-dependent transport hysteresis in conical nanopores or asymmetric nanointerfaces offer new opportunities for the selective transport of matter. This report shows that electro-osmotic flow (EOF) is an overlooked factor that increases ion selectivity while maintaining enhanced transport throughput in rectified nanoscale electrokinetic transport. The increased selectivity originates primarily from the suppression of anion flux by the fluid flow in the opposite direction under the applied electrical field. By solving the Poisson and Nernst–Planck (PNP) equations without and with coupled Navier–Stokes (PNP–NS) equations, the EOF effects on cation and anion transport are unequivocally revealed in asymmetric nanopipettes. The flux of cations and anions as well as the transference number and flow velocity are elucidated using the models and boundary conditions validated by previous experiments. A dimensionless parameter, radius over the Debye length, reveals optimal ion selectivity and energy cost at intermediate ion concentrations and nanopore sizes, up to hundreds of millimolars and tens of nanometers under time-dependent potential stimulus. Furthermore, the fundamental insights into EOF at nanointerfaces suggest new routes/strategies for better separation, analysis, and energy applications.

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

Phase Diagrams of Alloys and Their Hydrides via On-Lattice Graph Neural Networks and Limited Training Data

Efficient prediction of sampling-intensive thermodynamic properties is needed to evaluate material performance and permit high-throughput materials modeling for a diverse array of technology applications. To alleviate the prohibitive computational expense of high-throughput configurational sampling with density functional theory (DFT), surrogate modeling strategies like cluster expansion are many orders of magnitude more efficient but can be difficult to construct in systems with high compositional complexity. We therefore employ minimal-complexity graph neural network models that accurately predict and can even extrapolate to out-of-train distribution formation energies of DFT-relaxed structures from an ideal (unrelaxed) crystallographic representation. This enables the large-scale sampling necessary for various thermodynamic property predictions that may otherwise be intractable and can be achieved with small training data sets. Two exemplars, optimizing the thermodynamic stability of low-density high-entropy alloys and modulating the plateau pressure of hydrogen in metal alloys, demonstrate the power of this approach, which can be extended to a variety of materials discovery and modeling problems.

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

leapR: An R Package for Multiomic Pathway Analysis

A generalized goal of many high-throughput data studies is to identify functional mecha-nisms that underlie observed biological phenomena, whether disease outcomes or metabolic out-put. Increasingly, studies that rely on multiple sources of high-throughput data (genomic, tran-scriptomic, proteomic, metabolomic) are faced with a challenge of utilizing the data in a way that maximizes utility. However, methods for integration of multiple forms of molecular data into a biolog-ically coherent frameworks are needed. Furthermore, we have developed a framework to assess biological pathway activity that relates to phenotypic outcome using multi-source data. Availability and implementation: The leapR package with user manual and example workflow is available for download from GitHub (https://github.com/biodataganache/leapR).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Enhancing Top-Down Proteomics of Brain Tissue with FAIMS

Proteomic investigations of Alzheimer’s and Parkinson’s disease have provided valuable insights into neurodegenerative disorders. Thus far, these investigations have largely been restricted to bottom-up approaches, hindering the degree to which one can characterize a protein’s “intact” state. Top-down proteomics (TDP) overcomes this limitation, however it is typically limited to observing only the most abundant proteoforms and of a relatively small size. Therefore, offline fractionation techniques are commonly used to reduce sample complexity, limiting throughput. A higher throughput alternative is online fractionation, such as gas phase high-field asymmetric waveform ion mobility spectrometry (FAIMS). Using a high complexity sample derived from Alzheimer’s disease brain tissue, we describe how the addition of FAIMS to TDP can robustly improve the depth of proteome coverage. For example, implementation of FAIMS at -50 compensation voltage (CV) more than doubled the mean number of non-redundant proteoforms observed (1,833 ± 17, n = 3), compared to without (754 ± 35 proteoforms). We also found FAIMS can influence the transmission of proteoforms and their charge envelopes based on their size. Importantly, FAIMS enabled the identification of intact amyloid beta (Aß) proteoforms, including the aggregation-prone Aß1-42 variant which is strongly linked to Alzheimer’s disease.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Phase evolution and amorphous stability upon solid-state reaction in superlattice like Ge–Sb–Te combinatorial thin-film

In this paper, the superlattice-like (SLL) Ge–Sb–Te combinatorial thin films were prepared by using a high-throughput ion beam sputtering system. The phase evolution and amorphous stability of such films undergoing heat treatment as a function of the coating sequence and modulation period were systematically studied. The composition structure diagram was constructed via an automated process of data obtained by high-throughput synchrotron micro-X-ray diffraction and lab-based micro-X-ray fluorescence. Furthermore, the element distribution and microstructure in the depth direction of the SLL thin films were characterized with time-of-flight secondary ion mass spectrometry and transmission electron microscopy, respectively. These studies demonstrated that the coating sequence has a significant effect on the element distribution in the as-deposited SLL thin films and the structure of the final product upon solid-state reaction. Reducing the modulation period of the SLL thin film improves the stability of the amorphous Ge–Sb–Te phase. This work lays a solid foundation for the rational design of SLL Ge–Sb–Te thin films to improve their performance.

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

High Performing Inverted Flexible Perovskite Solar Cells via Solution Phase Deposition of Yttrium-Doped SnO 2 Directly on Perovskite

Solution processing of flexible perovskite solar cells (f-PSCs) provides an avenue for scalable, high-throughput printing of lightweight, scalable, and cost-effective flexible solar cells. However, the deposition of fully solution-processed metal oxide charge transport layers on perovskites has been limited by solvent incompatibilities and high processing temperatures for metal oxide nanoparticles. In this study, we present high-performance, inverted f-PSCs from the direct deposition of yttrium doped SnO 2 nanoparticles functionalized with acetate on top of perovskite as an ink in anhydrous ethanol via blade coating. Yttrium doping improved device performance by improving the charge extraction leading with a decreased series resistance leading to improvements in the open-circuit voltage and fill factor. Furthermore, the champion power conversion efficiency for 0.1 cm 2 devices increased from 14.3% for undoped SnO 2 to 18.2% with 2% Y:SnO 2 doping, which is unprecedented for f-PSCs on ITO-PET substrate employing SnO 2 as an ETL.

14 SOLAR ENERGY↗
DOE OSTI2024

Millimeter-Scale Exfoliation of hBN with Tunable Flake Thickness for Scalable Encapsulation

As a two-dimensional (2D) dielectric material, hexagonal boron nitride (hBN) is in high demand for applications in photonics, nonlinear optics, and nanoelectronics. Unfortunately, the high-throughput preparation of macroscopic-scale, high-quality hBN flakes with controlled thickness is an ongoing challenge, limiting device fabrication and technological integration. In this report we present a metal thin-film exfoliation method to prepare hBN flakes with millimeter-scale dimension, near-unity yields, and tunable flake thickness distribution from 1-7 layers, a substantial improvement over scotch tape exfoliation. The single crystallinity and high quality of the exfoliated hBN are demonstrated with optical microscopy, atomic force microscopy, Raman spectroscopy, and second harmonic generation. We further explore a possible mechanism for the effectiveness and selectivity based on thin-film residual stress measurements, density functional theory calculations, and transmission electron microscopy imaging of the deposited metal films. We find that the magnitude of the residual tensile stress induced by thin film deposition plays a key role in determining exfoliated flake thickness in a manner which closely resembles 3D semiconductor spalling. Lastly, we demonstrate that our exfoliated, large-area hBN flakes can be readily incorporated as encapsulating layers for other 2D monolayers. Altogether, this method brings us one step closer to the high throughput, mass production of hBN-based 2D photonic, optoelectronic, and quantum devices.

2D materials↗
DOE OSTI2021

Click-Chemistry-Based Free Azide versus Azido Sugar Detection Enables Rapid In Vivo Screening of Glycosynthase Activity

Engineering of carbohydrate-active enzymes such as glycosynthases to enable chemoenzymatic synthesis of bespoke oligosaccharides has been limited by the lack of suitable ultrahigh-throughput screening methods capable of robustly detecting either starting substrates or end-products of the glycosidic bond formation reaction. Currently, there are limited screening methods available for rapid and highly sensitive single-cell-based screening of glycosynthase enzymes employing azido sugars as activated donor glycosyl substrates. Here, we report a fluorescence-based approach employing click-chemistry for the selective detection of glycosyl azides as substrates versus free inorganic azides as reaction products that facilitated an ultrahigh-throughput in vivo single-cell-based assay of glycosynthase activity. This assay was developed based on the distinct differences observed in relative fluorescence intensity of the triazole-containing fluorophore product formed during the click-chemistry reaction of organic glycosyl azides versus inorganic azides. This discovery formed the basis for proof of concept validation of a directed evolution methodology for screening and sorting glycosynthase mutants capable of synthesis of targeted fucosylated oligosaccharides. Our screening approach facilitated fluorescence-activated cell sorting of an error-prone polymerase chain reaction-based mutant library of fucosynthases expressed in Escherichia coli to identify several novel mutants that showed increased activity for ß-fucosyl azide-activated donor sugars toward desired acceptor sugars (e.g., pNP-xylose and lactose). Finally, we discuss avenues for improving this proof of concept in vivo assay method to identify better glycosynthase mutants and further demonstrate the broader applicability of this screening methodology for synthesis of bespoke glycans.

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

Combinatorial Exploration and Mapping of Phase Transformation in a Ni–Ti–Co Thin Film Library

Combinatorial synthesis and high-throughput characterization of a Ni–Ti–Co thin film materials library are reported for exploration of reversible martensitic transformation. The library was prepared by magnetron co-sputtering, annealed in vacuum at 500 °C without atmospheric exposure, and evaluated for shape memory behavior as an indicator of transformation. Composition, structure, and transformation behavior of the 177 pads in the library were characterized using high-throughput wavelength dispersive spectroscopy (WDS), X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), and four-point probe temperature-dependent resistance (R(T)) measurements. A new, expanded composition space having phase transformation with low thermal hysteresis and Co > 10 at. % is found. Unsupervised machine learning methods of hierarchical clustering were employed to streamline data processing of the large XRD and XPS data sets. Through cluster analysis of XRD data, we identified and mapped the constituent structural phases. Finally, composition–structure–property maps for the ternary system are made to correlate the functional properties to the local microstructure and composition of the Ni–Ti–Co thin film library.

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

Pathways to Electrochemical Ironmaking at Scale Via the Direct Reduction of Fe 2 O 3

Electrochemical ironmaking can provide an energy efficient, zero-emissions alternative to traditional methods of ironmaking, but the scalability of low-temperature electrochemical cells may be constrained by reactor throughput and the availability of acceptable feedstocks. Electrodes directly converting solid iron-oxide particles to metal circumvent traditional mass-transport limitations but are sensitive to both the particle size and nanoscale morphology of reactants. Furthermore, the effect of these properties on reactor throughput has not been systematically studied at model electrowinning surfaces. Here, we have used size-controlled, homologous α-Fe 2 O 3 particles to study how the nanoscale morphology of oxides influences the obtainable current density toward Fe metal and integrated these results in a technoeconomic model for alkaline iron electrowinning systems. Micron-scale α-Fe 2 O 3 with nanoscale porosity can be used to form Fe at current densities commensurate with industrial water electrolysis (>0.6 A cm –2 ) in the absence of external convection, providing a path to cost-competitive and scalable ironmaking using electrochemistry.

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

Automated Redox Titrations via Interdigitated Electrode Arrays: Application to the Mediated Electron Transfer Interrogation of Charge and Rate on Electrodeposited Polymers

Mediated electron transfer (MET) plays a crucial role in energy storage and conversion technologies such as redox targeting flow batteries (RTFBs), yet its experimental investigation often requires labor-intensive and low-throughput setups. To address this, we developed a microfabricated interdigitated electrode array (IDA) platform that enables automated, high-throughput electrochemical redox titration measurement to be performed to study the MET process. Our redox titration method enables simultaneous measurement of the charge capacity and rate of MET processes on a material or surface. Automated redox titration (ART) facilitates systematic investigation of the MET process across a broad parameter space, exemplified through the study of polypyrrole (PPy) and a pyrene-4,5,9,10-tetrone azo group-based polymer (PTAP), both redox-active polymers relevant to various energy storage applications. Using PPy as a model material, 500 redox titration measurements were conducted within 50 h, varying the electrode gap widths, polymer charging potentials, voltammetric scan rates, and electrolyte concentrations. Finite-element simulations confirmed the electrochemical responses and elucidated the kinetics of the MET reactions. Our automated methodology was further tested with PTAP, revealing a surprising charging potential dependence on the rate of MET. The automation, flexibility, and scalability of our redox titration platform pave the way not only for advanced studies of MET processes relevant to RTFBs, but also with implications in the understanding of next-generation energy storage materials, molecular electrocatalysis, and biosensing.

electrochemical analysis↗
DOE OSTI2022

Melt Processing Pretreatment Effects on Enzymatic Depolymerization of Poly(ethylene terephthalate)

Poly(ethylene terephthalate) (PET) is a common thermoplastic material, used in a wide variety of applications (i.e., bottles, fabrics, packaging, electronics, and automotive components). Increasing demand for PET has precipitated a need for improved recycling technology, especially for single-use PET waste. Recently, enzymatic depolymerization has shown promise as an environmentally responsible alternative for PET chemical recycling that yields economically useful products (e.g., terephthalic acid, adipic acid, and ethylene glycol). However, the depolymerization system still suffers from low rates on crystalline PET substrates, and effects of realistic waste streams are not known. In our work, PET waste is pretreated using an ultra-high-speed twin-screw extruder system. PET substrates were modified by various processing pretreatments to allow enzymes better access to depolymerize substrate materials. The effect of varying throughput and mechanical shear on structural properties of the PET waste was analyzed using molecular weight and thermal characterizations. These pretreated samples exhibit modifications in molecular weight, glass transition temperature, crystallinity, and specific surface area. The unpurified leaf-branch compost cutinase enzyme produced from the fed-batch fermentation of Escherichia coli BL21(DE3) was used in enzymatic depolymerization, where a faster reaction was observed as crystallinity was decreased and the specific surface area was increased. The rate of terephthalic acid production was also significantly higher for samples processed at lower mechanical shear with higher throughputs. As a result, this work demonstrates the potential for tailoring pretreatments in pursuit of faster and more energy efficient PET recycling using enzymes, with facile adaptation to the industrial scale for the circular economy.

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

Isomerization and Selective Hydrogenation of Propyne: Screening of Metal–Organic Frameworks Modified by Atomic Layer Deposition

Various metal oxide clusters upward of 8 atoms (Cu, Cd, Co, Fe, Ga, Mn, Mo, Ni, Sn, W, Zn, In, and Al) were incorporated into the pores of the metal–organic framework (MOF) NU-1000 via atomic layer deposition (ALD) and tested via high-throughput screening for catalytic isomerization and selective hydrogenation of propyne. Cu and Co were found to be the most active for propyne hydrogenation to propylene, and synergistic bimetallic combinations of Co and Zn, along with standalone Zn and Cd, were established as the most active for conversion to the isomerized product, propadiene. The combination of Co and Zn in NU-1000 diminished the propensity for full hydrogenation to propane as well as coking compared to its individual components. Finally, this study highlights the potential for high-throughput screening to survey monometallic and bimetallic cluster combinations that best affect the efficient transformation of small molecules, while discerning mechanistic differences in isomerization and hydrogenation by different metals.

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

A Fast-Pass, Desorption Electrospray Ionization Mass Spectrometry Strategy for Untargeted Metabolic Phenotyping

Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) provides direct analytical readouts of small molecules that can be used to characterize the metabolic phenotypes of genetically engineered bacteria. In an effort to accelerate the time frame associated with the screening of mutant libraries, we have developed a high-throughput DESI-MSI analytical workflow implementing a single raster line-scan strategy that facilitates the collection of location-resolved molecular information from engineered strains on a subminute time scale. Evaluation of this “Fast-Pass” DESI-MSI phenotyping workflow on analytical standards demonstrated the capability of acquiring full metabolic profiling information with a throughput of ~40 s per sample. This Fast-Pass strategy was implemented in the analysis of genetically edited Escherichia coli strains that have been engineered to produce various free-fatty acids (FFAs) for applications relevant to biofuels. Due to the untargeted nature of DESI-MSI, the investigation of these strains yielded molecular information for both global metabolites and targeted detection of accumulated bioproducts, allowing simultaneous readouts of strain-specific chemical profiles and comparative measurements of FFA production levels.

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

Rapid Generation of Tandem Mass Spectrometry Reference Libraries Using Immediate Drop-on-Demand Liquid Handling Coupled to an Open Port Sampling Interface

In metabolomics, tandem MS (MS2) fragmentation libraries are important for the identification of unknown features, but generating these libraries takes many valuable hours of instrument and operator time. Here, an immediate droplet-on-demand/open port sampling interface was used to rapidly acquire tandem MS of standards arrayed in a 96-well plate format. A workflow was developed for automated, high-throughput control of MS2 library generation. Pure standard mass spectral libraries were collected on Orbitrap and Q-TOF mass spectrometers for 192 compounds using 6 different collision energies with a throughput of 4 and 7.8 s/spectrum, respectively. Libraries were acquired using different solvent additives, precursor adducts, and ion polarities.

Cahill, John [ORNL] (ORCID:0000000298664010)↗
DOE OSTI2021

Separating Physics and Dynamics Grids for Improved Computational Efficiency in Spectral Element Earth System Models

Previous studies have shown that atmospheric models with a spectral element grid can benefit from putting physics calculations on a relatively coarse finite volume grid. Here we demonstrate an alternative high-order, element-based mapping approach used to implement a quasi-equal-area, finite volume physics grid in E3SM. Unlike similar methods, the new method in E3SM requires topology data purely local to each spectral element, which trivially allows for regional mesh refinement. Simulations with physics grids defined by 2 × 2, 3 × 3, and 4 × 4 divisions of each element are shown to verify that the alternative physics grid does not qualitatively alter the model solution. The model performance is substantially affected by the reduction of physics columns when using the 2 × 2 grid, which can increase the throughput of physics calculations by roughly 60%–120% depending on whether the computational resources are configured to maximize throughput or efficiency. A pair of regionally refined cases are also shown to highlight the refinement capability.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Identification of beneficial and detrimental bacteria impacting sorghum responses to drought using multi-scale and multi-system microbiome comparisons

Abstract Drought is a major abiotic stress limiting agricultural productivity. Previous field-level experiments have demonstrated that drought decreases microbiome diversity in the root and rhizosphere. How these changes ultimately affect plant health remains elusive. Toward this end, we combined reductionist, transitional and ecological approaches, applied to the staple cereal crop sorghum to identify key root-associated microbes that robustly affect drought-stressed plant phenotypes. Fifty-three Arabidopsis-associated bacteria were applied to sorghum seeds and their effect on root growth was monitored. Two Arthrobacter strains caused root growth inhibition (RGI) in Arabidopsis and sorghum. In the context of synthetic communities, Variovorax strains were able to protect plants from Arthrobacter-caused RGI. As a transitional system, high-throughput phenotyping was used to test the synthetic communities. During drought stress, plants colonized by Arthrobacter had reduced growth and leaf water content. Plants colonized by both Arthrobacter and Variovorax performed as well or better than control plants. In parallel, we performed a field trial wherein sorghum was evaluated across drought conditions. By incorporating data on soil properties into the microbiome analysis, we accounted for experimental noise with a novel method and were able to observe the negative correlation between the abundance of Arthrobacter and plant growth. Having validated this approach, we cross-referenced datasets from the high-throughput phenotyping and field experiments and report a list of bacteria with high confidence that positively associated with plant growth under drought stress. In conclusion, a three-tiered experimental system successfully spanned the lab-to-field gap and identified beneficial and deleterious bacterial strains for sorghum under drought.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Low cost and massively parallel force spectroscopy with fluid loading on a chip

Current approaches for single molecule force spectroscopy are typically constrained by low throughput and high instrumentation cost. Herein, a low-cost, high throughput technique is demonstrated using microfluidics for multiplexed mechanical manipulation of up to ~4000 individual molecules via molecular fluid loading on-a-chip (FLO-Chip). The FLO-Chip consists of serially connected microchannels with varying width, allowing for simultaneous testing at multiple loading rates. Molecular force measurements are demonstrated by dissociating Biotin-Streptavidin and Digoxigenin-AntiDigoxigenin interactions along with unzipping of double stranded DNA of varying sequence under different dynamic loading rates and solution conditions. Rupture force results under varying loading rates and solution conditions are in good agreement with prior studies, verifying a versatile approach for single molecule biophysics and molecular mechanobiology. FLO-Chip enables straightforward, rapid, low-cost, and portable mechanical testing of single molecules that can be implemented on a wide range of microscopes to broaden access and may enable new applications of molecular force spectroscopy.

42 ENGINEERING↗