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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Aerosol impacts on isolated deep convection: findings from TRACER

This study focuses on quantifying the conditional relationship between aerosol and convective precipitation properties of isolated deep convective clouds (DCCs) in the Houston–Galveston region, after adjusting for confounding effects. We leverage comprehensive ground-based observations from the TRacking Aerosol Convection interactions ExpeRiment (TRACER) to estimate aerosol effects on convective echo top height (ETH), intensity, and area separately. Our results show that greater aerosol number concentrations generally have a limited impact on these convective properties, showing relationships consistent with the possibility of both invigoration and suppression effects. Under certain conditions, where ultrafine particles are abundant, aerosols exhibit a positive effect on ETH, increasing it by about 1 km. However, it is inevitable to consider measurement uncertainties and the limitations of temporal and spatial resolution in the data, as these factors can further contribute to uncertainties in our estimates. In DCCs associated with sea breezes, the estimated aerosol effects on DCCs are found to be more pronounced. However, this heightened effect could be attributed to the exclusion of key confounders such as boundary layer updrafts in the analysis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Transactive Emergency Power Allocation

The devastating impacts of extreme weather events, many of which are climate-change related, are increasingly evident through the frequency and duration of outages on power grids, especially the distribution systems. One of the major modern-day concerns of utilities is dealing with such extreme supply outages where operators have used rolling blackouts as a contingency plan balance supply and demand while serving critical loads. Such events have significant repercussions social and economic costs. Such blackouts practices are a blunt instrument, depriving customers with low-capacity high-priority loads (i.e. refrigeration, water, telecommunication, etc.) that provide high marginal amenity. Our contribution presented in this work is a transactive emergency allocation mechanism that would provide some minimum level of service to all of the customers while enabling preference-based trading of this initial allocation. This is in contrast to the state-of-art TE mechanisms that allocate resources to customers solely based on their willingness-to-pay. The effectiveness of the proposed mechanism is demonstrated through simulation-based evaluation on a prototypical distribution system experiencing 12-hour scarcity-based emergency event due to extreme operating conditions. Simulation results clearly demonstrate the capability of the proposed transactive emergency allocation mechanism in effectively utilizing the available energy and providing some level of service to all customers to operate their high-priority loads throughout the extreme scarcity event while being economically efficient in allowing trading of allocation based on customer preferences.

transactive energy, power system economics, emerge↗
DOE OSTI2022

Data-driven, multi-moment fluid modeling of Landau damping

Deriving governing equations of complex physical systems based on first principles can be quite challenging when there are certain unknown terms and hidden physical mechanisms in the systems. In this work, we apply a deep learning architecture to learn fluid partial differential equations (PDEs) of a plasma system based on the data acquired from a fully kinetic model. Here, the learned multi-moment fluid PDEs are demonstrated to incorporate kinetic effect such as Landau damping. Based on the learned fluid closure, the data-driven, multi-moment fluid modeling can well reproduce all the physical quantities derived from the fully kinetic model. The calculated damping rate of Landau damping is consistent with both the fully kinetic simulation and the linear theory. The data-driven fluid modeling of PDEs for complex physical systems may be applied to improve the fluid closure and reduce the computational cost of multi-scale modeling of global systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Three-dimensional cooperative inversion of airborne magnetic and gravity gradient data using deep-learning techniques

Using multiple geophysical methods has become a prevailing approach in numerous geophysical applications to investigate subsurface structures and parameters. These multimethod-based exploration strategies have the potential to greatly diminish uncertainties and ambiguities encountered during geophysical data analysis and interpretation. One of the applications is the cooperative inversion of airborne magnetic and gravity gradient data for the interpretation of data obtained in mineral, oil and gas, and geothermal explorations. In this paper, a unified cooperative inversion framework is designed by combining the standard separate inversions with a deep neural network (DNN), which serves as the link between different types of data. A well-trained DNN takes the separately inverted susceptibility and density models as the inputs and provides improved models that will be used as the initial models of deterministic inversions. A two-round iteration strategy is adopted to guarantee the reasonability of the recovered models and overall efficiency of the inversion. In addition, this deep-learning (DL)-based framework demonstrates excellent generalization abilities when tested on models that are entirely distinct from the training data sets. The framework can easily incorporate multiphysics without necessitating any structural changes to the network. Synthetic experiments validate that our DL-based method outperforms conventional separate inversions and cross-gradient-based joint inversion in view of the accuracy of the recovered models and inversion efficiency. Successful application to field data further verifies the effectiveness of our DL-based method.

Geochemistry & Geophysics↗
DOE OSTI2020

Effects of graphene surface functionalities towards controlled reinforcement of a lignin based renewable thermoplastic rubber

In this report, we describe methods to enhance mechanical properties of a renewable thermoplastic rubber by incorporating functional graphene platelets into an equal-mass mixture of lignin, a feedstock from plant biomass, and a nitrile-butadiene rubber having 41 mol % acrylonitrile content (NBR41) that form a nanocomposite. Not all lignins yield mechanically strong material when they are combined with NBR41, and thus, limit its use for such rubbery products. Here, we evaluate different graphene oxides (GO) and reduced graphene oxides (rGO) dry-powders with different surface areas, functionality, and wettability in the synthesis of performance-enhanced nanocomposites of soft lignin/NBR41 matrix via a solvent-free, high shear reactive process. High surface area GO (HSGO) platelets with strong hydrophilicity exhibit good dispersion in the multiphase lignin/NBR41 composites with lignin dispersion varying from 200 to 2000 nm, resulting in superior reinforcement over other graphene derivatives. The addition of 1–4 wt % HSGO increased the tensile stress of the lignin/NBR41 thermoplastic rubber matrix by 60–160% (15–24 MPa) and the modulus by 200–700% (60–140 MPa). Scanning electron microscopy and small angle X-ray scattering results show that the well-dispersed HSGO platelets effectively disrupt the lignin-rich aggregates in NBR41 matrix, resulting in both strength and stiffness enhancements in the formed nanocomposites. This report on performance enhancement of lignin-based renewable polymers via the production of nanocomposite would increase potential for ‘finding the value of lignin’—a grand challenge associated with modern biorefineries.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Exploring Catalyst Compositions for Microwave-Assisted Methane Dehydroaromatization

The flaring of natural gas in U.S. shale regions remains a challenge for producers. One alternative to flaring is converting the wasted gas into valuable chemicals. Microwave-based processes offer a promising solution, potentially enabling the development of compact, modular systems for on-site production of chemicals, such as aromatics, from natural gas. This is due to the advantages of microwave heating, including efficient heating of compact volumes, accelerated reaction rates, and electrification of heating. However, developing effective catalysts for microwave-based processes is challenging, as conventional materials often require modification to be effectively heated by microwaves. This study provides an overview of a catalyst development project focused on a molybdenum-supported zeolite catalyst, optimized for the direct conversion of methane into aromatics under microwave irradiation. It details the synthesis, characterization, and the effects of promoters, as well as computational efforts undertaken to understand and enhance the catalyst's performance.

flare gas↗
DOE OSTI2024

Misaligned Wind‐Waves Behind Atmospheric Cold Fronts

Abstract Atmospheric fronts embedded in extratropical cyclones are high‐impact weather phenomena, contributing significantly to mid‐latitude winter precipitation. The three vital characteristics of the atmospheric fronts, high wind speeds, abrupt change in wind direction, and rapid translation, force the induced surface waves to be misaligned with winds exclusively behind the cold fronts. The effects of the misaligned waves under atmospheric cold fronts on air‐sea fluxes remain undocumented. Using the multi‐year in situ near‐surface observations and direct covariance flux measurements from the Pioneer Array off the coast of New England, we find that the majority of the passing cold fronts generate misaligned waves behind the cold front. Once generated, the waves remain misaligned, on average, for about 8 hr. The parameterized effect of misaligned waves in a fully coupled model significantly increases the roughness length (185%), drag coefficient (19%), and air‐sea momentum flux (11%). The increased surface drag reduces the wind speeds in the surface layer. The upward turbulent heat flux is weakly decreased by the misaligned waves because of the decrease in temperature and humidity scaling parameters being greater than the increase in friction velocity. The misaligned wave effect is not accurately represented in a commonly used wave‐based bulk flux algorithm. Yet, considering this effect in the current formulation improves the overall accuracy of parameterized momentum flux estimates. The results imply that better representing a directional wind‐wave coupling in the bulk formula of the numerical models may help improve the air‐sea interaction simulations under the passing atmospheric fronts in the mid‐latitudes.

Oceanography↗
DOE OSTI2020

Tunable analog thermal material

Naturally-occurring thermal materials usually possess specific thermal conductivity ($\textit{κ}$), forming a digital set of $\textit{κ}$ values. Emerging thermal metamaterials have been deployed to realize effective thermal conductivities unattainable in natural materials. However, the effective thermal conductivities of such mixing-based thermal metamaterials are still in digital fashion, i.e., the effective conductivity remains discrete and static. Here, we report an analog thermal material whose effective conductivity can be in-situ tuned from near-zero to near-infinity $\textit{κ}$. The proof-of-concept scheme consists of a spinning core made of uncured polydimethylsiloxane (PDMS) and fixed bilayer rings made of silicone grease and steel. Thanks to the spinning PDMS and its induced convective effects, we can mold the heat flow robustly with continuously changing and anisotropic $\textit{κ}$. Our work enables a single functional thermal material to meet the challenging demands of flexible thermal manipulation. It also provides platforms to investigate heat transfer in systems with moving components.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Nucleon-nucleon potentials from Δ-full chiral effective-field-theory and implications

We closely investigate NN potentials based upon the Δ-full version of chiral effective-field-theory. We find that recently constructed NN potentials of this kind, which (when applied together with three-nucleon forces) were presented as predicting accurate binding energies and radii for a range of nuclei from A = 16 to A = 132 and providing accurate equations of state for nuclear matter, yield a χ 2 /datum of 60 for the reproduction of the pp data below 100 MeV laboratory energy. This χ 2 is more than three times what the Hamada-Johnston potential of the year of 1962 achieved already some 60 years ago. We perceive this historical fact as concerning in view of the current emphasis on precision. We are able to trace the very large χ 2 as well as the apparent success of the potentials in nuclear structure to unrealistic predictions for P-wave states, in which the Δ-full next-to-next-to-leading order (NNLO) potentials are off by up to 40 times the NNLO truncation errors. In fact, we show that the worse the description of the P-wave states, the better the predictions in nuclear structure. Thus, these potentials cannot be seen as the solution to the outstanding problems in current microscopic nuclear structure physics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Effects of CELF Pretreatment Severity on Lignin Structure and the Lignin-Based Polyurethane Properties

Conversion of technical lignin into performance biopolymers such as polyurethane offers environmental and economic advantages when combined with production of biofuels from biomass sugars, presenting significant interest toward studying the role of pretreatment on lignin structure and functionality. Co-solvent enhanced lignocellulosic fractionation (CELF) pretreatment, employing acidic aqueous tetrahydrofuran (THF) mixtures, was developed to effectively break down the lignin-carbohydrate matrix and promote extraction of lignin from lignocellulosic biomass with desirable purity and yield. In this study, we report the effects of CELF pretreatment reaction severity on the molecular structure of CELF-extracted lignin and its impact toward the mechanical properties of the resulting lignin-based polyurethanes. Reaction temperature was found to play the most significant role, compared to reaction time and acidity, in manipulating structural features such as molecular weight, functionality and intra-polymer structure. At the severe reaction conditions at 180°C, the order of reactivity for primary lignin interlinkages characterized by semiquantitative HSQC NMR analysis were found to be β-ether > phenylcoumaran (β−5′) > resinol (β−β′) facilitating a high degree of depolymerization and yielding a high frequency of free phenolics and reduced aliphatic hydroxyl groups. All side-chain interlinkages were depleted converting guaiacyl subunits into condensed forms, while still retaining uncondensed syringyl subunits. Under the mild 150°C temperature reaction, CELF lignin had higher molecular weight and retained more β-ether interlinkages. The results from CELF lignin-based polyurethane synthesis indicated that the tensile properties depended on the miscibility of CELF lignin with other components and low molecular weight cuts improved the dispersion of lignin in the polyurethane network. Pre-mixing of CELF with poly(ethylene glycol) (PEG) reduced the brittleness and improved the ductility of the CELF lignin-PEG polyurethanes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Trace-Level, Multi-Gas Detection for Food Quality Assessment Based on Decorated Silicon Transistor Arrays

Multiplexed gas detection at room temperature is critical for practical applications, such as for tracking the complex chemical environments associated with food decomposition and spoilage. Here, an integrated array of multiple silicon-based, chemical-sensitive field effect transistors (CSFETs) is presented to realize selective, sensitive, and simultaneous measurement of gases typically associated with food spoilage. CSFETs decorated with sensing materials based on ruthenium, silver, and silicon oxide are used to obtain stable room-temperature responses to ammonia (NH 3 ), hydrogen sulfide (H 2 S), and humidity, respectively. For example, one multi-CSFET sensor signal changes from its baseline by 13.34 in response to 1 ppm of NH 3 , 724.45 under 1 ppm H 2 S, and 23.46 under 80% relative humidity, with sensitive detection down to 10 ppb of NH 3 and H 2 S. To demonstrate this sensor for practical applications, the CSFET sensor array is combined with a custom-printed circuit board into a compact, fully integrated, and portable system to conduct real-time monitoring of gases generated by decomposing food. By using existing silicon-based manufacturing methodologies, this room-temperature gas sensing array can be fabricated reproducibly and at low cost, making it an attractive platform for ambient gas measurement needed in food safety applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Marine Algae Industrialization Consortium (MAGIC): Combining biofuel and high-value bioproducts to meet the RFS

The Marine Algae Industrialization Consortium (MAGIC) was formed to address pressing challenges in the commercialization of microalgae as a source of biofuel. The “Marine Algae Industrialization Consortium (MAGIC): Combining biofuel and high-value bioproducts to meet the RFS” project formally addressed two US Department of Energy Bioenergy Technologies Office (BETO) goals: (1) Model the sustainable supply of 1 million metric tonnes ash free dry weight (AFDW) cultivated algal biomass and (2) Demonstrate valuable co-products produced along with biofuel intermediates to increase value of algal biomass by 30%. To achieve these goals, the project demonstrated and validated high-value co-products to drive down the cost of biofuel by increasing the value of algae “co-products” towards increasing the selling price of total algae biomass as one of the key drivers of economics and adoption. This was accomplished through five core, interdependent tasks including: (1) strain selection to identify and deliver strains for mass culture, (2) mass culture using a hybrid cultivation system and following key operating parameters for downstream applications to provide algae feedstock, (3) recovery and conversion to evaluate two alternative methods to separate dry algae biomass into oil and residuals for downstream testing, (4) product assessment to determine biofuel, aquafeed or poultry feed product efficacy using algae biomass fractions as well as to provide critical performance data for valuation and (5) commercialization to use technoeconomic and life cycle assessments (TEA/LCA) as iterative design and assessment tools including consideration of target markets, competitors, and distribution channels to guide product assessment, development and valuation. A total of 46 peer-review publications, many open-access, provide detail of much of the work carried out and the results of the tasks. Additional reports and presentations provide other technical and public engagement material. At a high level, using a variety of approaches, more than 1000 marine microalgae strains were evaluated to ultimately identify the seven winners that were down-selected to be grown in mass culture. Strain selection demonstrated that there were no ‘super strains’ and that each candidate had strengths and limitations for specific products, growth conditions or operational considerations. Mass culture growth of these seven strains at >5000 L / 29 m 2 scale found that four them were suitable for product assessment. More than 250 kg of biomass was produced across hundreds of pond runs along with thousands of cultivation entries on the growth and biomass characteristics as well as environmental parameters. In the process, dozens of standard operating procedures were generated as was custom software to process and analyze cultivation data. Recovery and conversion of algae biomass demonstrated that a hexane solvent based extraction protocol was most effective at recovering oil (biocrude) from algae and four strains were processed to produce oil and lipid extracted algae (residuals) for downstream testing. Membrane-based oil separation was less successful, but may still be applicable to other commercial applications in the future. Product testing demonstrated that algae biocrude is of high quality and hydrotreating generated numerous fractions of high quality composition for fuel and lubricate based applications. Aquafeed studies performed at a variety of scales showed that both whole and defatted (lipid extracted algae) microalgae were suitable as a feed ingredient, but that the specifics of the fed animal and biochemical composition of the algae are critical factors when determining formulation. Similarly, poultry studies on whole and defatted microalgae generally showed positive outcomes on animal growth and health, with some microalgae providing enhanced nutritional composition of the animal product. Economic and life cycle assessments covered a wide range of possible commercialization and sustainability scenarios. Replacement value, improved product value added, consumer values marketing added valuation and improved animal health were considered as alternatives for microalgae valuation. Using the open pond system, algae productivity was identified as the key driver of commercialization economics, but combination of co-products (e.g. animal feed) with biofuel production substantially increased the total selling price of algae. Modeled microalgae selling price exceeded $\$$1500/tonne and could generate competitive biofuel selling prices below $\$$5 gallon gas equivalents using realistic algal productivities. Short (process scale) and longer (decadal trends) sustainability assessments show that marine microalgae can enhance the sustainability of energy production and lead to other realized benefits in water, fertilizer and land use for other sectors (e.g. agriculture). This project successfully demonstrated all of the components of an end-to-end process from mass microalgae cultivation and dewatering, to recovery and conversion of algae biomass components, to final product demonstration and process valuation; the combined results provide a framework for future commercialization of algae based biofuels.

09 BIOMASS FUELS↗
DOE OSTI2023

Deep learning of electrochemical CO 2 conversion literature reveals research trends and directions

Large-scale and openly available material science databases are mainly composed of computer simulation results rather than experimental data. Some examples include the Materials Project, Open Quantum Materials Database, and Open Catalyst 2022. Unfortunately, building large-scale experimental databases remains challenging due to the difficulties in consolidating locally distributed datasets. In this work, focusing on the catalysis literature of CO 2 reduction reactions (CO 2 RRs), we present a machine learning (ML)-based protocol for selecting highly relevant papers and extracting important experimental data. First, we report a document embedding method (Doc2Vec) for collecting papers of greatest relevance to the specific target domain, which yielded 3154 CO 2 RR-related papers from six publishers. Next, we developed named entity recognition (NER) models to extract twelve entities related to material names (catalyst, electrolyte, etc.) and catalytic performance (Faradaic efficiency, current density, etc.). Further, among several tested models, the MatBERT-based approach achieved the highest accuracy, with an average F1-score of 90.4% and an F1-score of 95.2% in a boundary relaxation evaluation scheme. The accurate and accelerated NER-based data extraction from a large volume of catalysis literature enables temporal trend analyses of the CO 2 RR catalysts, products, and performances, revealing the potentially effective material space in CO 2 RRs. While this work demonstrates the effectiveness of our ML-based text mining methods for specifically CO 2 RR literature, the methods and approach are applicable to and may be used to accelerate the development of other catalytic chemical reactions.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Silica-modifying chemical admixtures for directed zeolitization of metakaolin-based alkali-activated materials

The effect of using trimethyladamantyl-ammonium hydroxide (TMAAOH) as a silica-modifying admixture to induce early-age mineralization during alkali-activation of metakaolin was investigated and reported herein. In all material formulations, the use of TMAAOH induced early-age mineralization, increased mixture stiffening in the fresh state, and lowered total heat of reaction. In activating solutions with silica moduli above unity (Ms >1.0), mineralogy results demonstrate that TMAAOH induces the nucleation and growth of metastable zeolitic phases, which correlated with increased permeability and increased plastic shrinkage of the paste. When TMAAOH was added to activating solutions with silica moduli near unity (Ms ~1.0), the controlled formation of crystalline, silica-rich faujasite was observed, which correlated with reduced permeability and lower plastic shrinkage. Together, these results demonstrate for the first time that silica-templating agents such as TMAAOH can be exploited in the design of new chemical admixtures that directly influence the dynamics of zeolitization in alkali-activated materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

An advanced low-cost cathode composed of graphene-coated Na 2.4 Fe 1.8 (SO 4 ) 3 nanograins in a 3D graphene network for ultra-stable sodium storage

Iron-based electrodes have attracted great attention for sodium storage because of the distinct cost effectiveness. However, exploring suitable iron-based electrodes with high power density and long duration remains a big challenge. Herein, a spray-drying strategy is adopted to construct graphene-coated Na 2.4 Fe 1.8 (SO 4 ) 3 nanograins in a 3D graphene microsphere network. The unique structural and compositional advantages endow these electrodes to exhibit outstanding electrochemical properties with remarkable rate performance and long cycle life. Additionally, mechanism analyses further explain the outstanding electrochemical properties from the structural aspect.

25 ENERGY STORAGE↗
DOE OSTI2020

Comparing Experimental Phase Behavior of Ion-Doped Block Copolymers with Theoretical Predictions Based on Selective Ion Solvation

The effects of salt-doping on the morphological behavior of block copolymers are well established but remain poorly understood, partially because of the challenge of resolving electrostatics in a heterogeneous medium with low average permittivity. By employing a recently developed field theory, we analyze the phase behavior of polystyrene-b-poly(ethylene oxide) (SEO) copolymers doped with lithium bis(trifluoromethanesulfonyl)imide salts (LiTFSI). Using a single fitting parameter, the ionic solvation radius, we obtain qualitative agreement between our theory and experimental data over a range of polymer molecular weights and copolymer compositions. Such agreement supports and highlights the need of solvation free energy to accurately describe the self-assembly of ion-doped block copolymers and demonstrates that experimentally observed dependence on molecular weight, not present in neutral block copolymers, can be rationalized by solvation effects. Overall, morphological variations are stronger than those predicted by the leading, linear order theory but can be captured by the full model.

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

KTaO 3 -Based Supercurrent Diode

The supercurrent diode effect (SDE), characterized by nonreciprocal critical currents, represents a promising building block for future dissipationless electronics and quantum circuits. Realizing SDE requires breaking both time-reversal and inversion symmetry in the device. Here we use conductive atomic force microscope (c-AFM) lithography to pattern reconfigurable superconducting weak links (WLs) at the LaAlO 3 /KTaO 3 (LAO/KTO) interface. By deliberately engineering the WL geometry at the nanoscale, we realize SDE in these devices in the presence of modest out-of-plane magnetic fields. The SDE polarity can be reversed by simply changing the WL position, and the rectification efficiency reaches up to 13% under optimal magnetic field conditions. Time-dependent Ginzburg–Landau simulations reveal that the observed SDE originates from asymmetric vortex motion in the inversion-symmetry-breaking device geometry. This demonstration of SDE in the LAO/KTO system establishes a versatile platform for investigating and engineering vortex dynamics, forming the basis for engineered quantum circuit elements.

C-AFM lithography↗
DOE OSTI2023

A streamlined tandem tip-based workflow for sensitive nanoscale phosphoproteomics

Effective phosphoproteome of nanoscale sample analysis remains a daunting task, primarily due to significant sample loss associated with non-specific surface adsorption during enrichment of low stoichiometric phosphopeptide. We develop a tandem tip phosphoproteomics sample preparation method that is capable of sample cleanup and enrichment without additional sample transfer, and its integration with our recently developed SOP (Surfactant-assisted One-Pot sample preparation) and iBASIL (improved Boosting to Amplify Signal with Isobaric Labeling) approaches provides a streamlined workflow enabling sensitive, high-throughput nanoscale phosphoproteome measurements. This approach significantly reduces both sample loss and processing time, allowing the identification of >3000 (>9500) phosphopeptides from 1 (10) µg of cell lysate using the label-free method without a spectral library. It also enables precise quantification of ~600 phosphopeptides from 100 sorted cells (single-cell level input for the enriched phosphopeptides) and ~700 phosphopeptides from human spleen tissue voxels with a spatial resolution of 200 µm (equivalent to ~100 cells) in a high-throughput manner. The new workflow opens avenues for phosphoproteome profiling of mass-limited samples at the low nanogram level.

59 BASIC BIOLOGICAL SCIENCES↗