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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Structural Study of Analogues of Titan’s Haze by Trapped Ion Mobility Coupled with a Fourier Transform Ion Cyclotron Mass Spectrometer

The aerosols present in the atmosphere of the Saturn’s moon Titan are of particular planetary science interest and several spacecraft missions are already allowed to gather spectroscopic data. Titan haze’s analogs, so-called tholins, were produced on earth to push forward the comprehension of their formation and properties. In this study, this highly complex mixture was analyzed here for the first time by trapped ion mobility spectrometry coupled to ultra-high resolution mass spectrometry (FTICR MS). Electrospray ionization revealed the characteristic CHN{sub x}-class components, with CHN{sub 5–6} and DBE 6–7 most abundant. Deploying specialized visualization, enabled by accurate mass measurements and elemental composition assignments, the adapted Kendrick mass defect analysis highlights the C{sub 2}H{sub 3}N homolog series, whereas the nitrogen-modified van Krevelen diagram exhibits a clear trend towards H/C 1.5 and N/C 0.5. More interestingly, the representation of m/z versus collision cross section (CCS) allowed hypothesizing a ramified N-PAH structural motif. State-of-the-art IMS is currently not able to resolve the isomeric continuum of ultra-complex mixtures; thus, peak parameters other than the CCS value are explored. As such, analyzing the mobility peak width versus m/z shows a linear increase in isomeric diversity between m/z 170 and 350 and a near plateau in diversity at higher m/z for the N-PAH-like structure. Due to the high complexity of the sample, these structural insights are only to be revealed by TIMS-FTICR MS. .

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Assessment of two benzylation strategies for the analysis of nerve-agent derived ethyl- and pinacolyl methyl phosphonic acids in sandy loam soil by GC–MS

Despite their prohibition by the Chemical Weapons Convention, nerve agents (NAs) remain in use against military and civilian targets. Due to their high reactivity, NAs readily degrade to phosphonic acids, making them important markers in the inspection of areas of presumed NA use. In this work, we assess the use of benzylation to modify ethyl- and pinacolyl methylphosphonic acids, degradation products of VX and Soman respectively, for their efficient detection in a soil matrix at ~10 and ~1 μg/g using GC–MS. The soil matrix, Sandy Loam (SL), was chosen for its ubiquitous nature, complex composition with silica particles embedded in clay, and low organic content. In this study, we demonstrate that benzylation via benzyl bromide yields a LOD = 25.6 ng/mL for benzylated-EMPA and LOD = 30.1 ng/mL for benzylated-PMPA. This is superior to the use of p-methoxybenzyl trichloroacetimidate in providing stable phosphonic acid ester derivatives for analysis. A base-modified procedure for p-methoxybenzylation was explored in this study yielding a LOD = 29.1 ng/mL for p-methoxybenzylated-EMPA and LOD = 39.8 ng/mL for p-methoxybenzylated-PMPA. Both benzylation pathways (benzyl bromide and p-methoxybenzyl trichloroacetimidate) can be used to yield phosphonic acid derivatives that provide further confirmation of these Soman and VX degradation products in soil samples in investigative scenarios. The work herein represents the first application of benzylation methods for the analysis of these NA markers in the acidic, silicon-based SL soil.

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

A Bayesian Approach for Quantifying Data Scarcity when Modeling Human Behavior via Inverse Reinforcement Learning

Computational models that formalize complex human behaviors enable study and understanding of such behaviors. However, collecting behavior data required to estimate the parameters of such models is often tedious and resource intensive. Thus, estimating dataset size as part of data collection planning (also known as Sample Size Determination) is important to reduce the time and effort of behavior data collection while maintaining an accurate estimate of model parameters. In this paper, we present a sample size determination method based on Uncertainty Quantification (UQ) for a specific Inverse Reinforcement Learning (IRL) model of human behavior, in two cases: 1) pre-hoc experiment design—conducted in the planning stage before any data is collected, to guide the estimation of how many samples to collect; and 2) post-hoc dataset analysis—performed after data is collected, to decide if the existing dataset has sufficient samples and whether more data is needed. Here, we validate our approach in experiments with a realistic model of behaviors of people with Multiple Sclerosis (MS) and illustrate how to pick a reasonable sample size target. Our work enables model designers to perform a deeper, principled investigation of effects of dataset size on IRL.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Discovery and analysis of a potential blind geothermal system in southern Gabbs Valley, western Nevada

The southern Gabbs Valley geothermal prospect is a blind thermal anomaly located 5 km north of the Gabbs Valley Range and ~15 km southeast of the Don A. Campbell geothermal power plant in west-central Nevada. The discovery of this blind thermal anomaly was initiated from the development of a detailed geothermal potential map covering 96,000 km2 of the Great Basin region. This map synthesized about 9 geologic and geophysical parameters and showed high geothermal potential in southern Gabbs Valley. Subsequent geologic reconnaissance identified areas of favorable structure for hosting a blind geothermal system. Areas displaying complex fault relationships were then targeted for further exploration utilizing a shallow 2-meter thermal survey. The first 2-meter survey incorporated 60 data points in the basin, with one anomalously high temperature point located in the southern portion of the basin. Water samples were taken from the Diamond A ranch 6 km northwest of the thermal anomaly. These samples yielded a geothermometer of 130-140°C. Additional shallow temperature survey work has been completed constraining the extent of the thermal anomaly and establishing a 7 km2 area with elevated 2-meter temperatures. Subsurface data generated from a new gravity survey show that the 2-meter thermal anomaly corresponds to a significant gravity gradient that probably reflects a subsurface fault and possible fault intersection. Exploration of the system is ongoing, and further detailed mapping of bedrock and Quaternary exposures in the area will aid in understanding the structural controls of this potential geothermal system. The integration of geochemical, geophysical, and geologic datasets in this area will elucidate the probability of a commercial-grade geothermal system and produce a conceptual model to be used in the selection of possible drill targets.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Enabling machine learning-ready HPC ensembles with Merlin

With the growing complexity of computational and experimental facilities, many scientific researchers are turning to machine learning (ML) techniques to analyze large scale ensemble data. With complexities such as multi-component workflows, heterogeneous machine architectures, parallel file systems, and batch scheduling, care must be taken to facilitate this analysis in a high performance computing (HPC) environment. Here, we present Merlin, a workflow framework to enable large ML-friendly ensembles of scientific HPC simulations. By augmenting traditional HPC with distributed compute technologies, Merlin aims to lower the barrier for scientific subject matter experts to incorporate ML into their analysis. As a producer–consumer workflow model, Merlin enables multi-machine, cross-batch job, dynamically allocated yet persistent workflows capable of utilizing surge-compute resources. Key features of Merlin are a flexible HPC-centric interface, low per-task overhead, multi-tiered fault recovery, and a hierarchical sampling algorithm that allows for $\mathscr{O}$(N) task execution and $\mathscr{O}$(N ln N) task queuing to ensembles of millions of tasks. In addition to Merlin’s design, we test the algorithm’s performance in an HPC center and demonstrate the ability to enqueue 40 million simulations in 100 s, with a 30 millisecond per-task overhead that is independent of ensemble size. Finally, we describe some example applications that Merlin has enabled on leadership-class HPC resources, such as the ML-augmented optimization of nuclear fusion experiments and the calibration of infectious disease models to study the progression of and possible mitigation strategies for COVID-19.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Impact of Thermal Pretreatment Temperatures on Woody Biomass Chemical Composition, Physical Properties and Microstructure

Thermal pretreatment of biomass by torrefaction and low temperature pyrolysis has the potential for generating high quality and more suitable fuels. To utilize a model to describe the complex and dynamic changes taking place during these two treatments for process design, optimization and scale-up, detailed data is needed on the property evolution during treatment of well-defined individual biomass particles. The objectives of this study are to investigate the influence of thermal pretreatment temperatures on wood biomass biochemical compositions, physical properties and microstructure. Wild cherry wood was selected as a model biomass and prepared for this study. The well-defined wood particle samples were consecutively heated at 220, 260, 300, 350, 450 and 550 °C for 0.5 h under nitrogen. Untreated and treated samples were characterized for biochemical composition changes (cellulose, hemicellulose, and lignin) by thermogravimetric analyzer (TGA), physical properties (color, dimensions, weight, density and grindablity), chemical property (proximate analysis and heating value) and microstructural changes by scanning electron microscopy (SEM). Hemicellulose was mostly decomposed in the samples treated at 260 and 300 °C and resulted in the cell walls weakening resulting in improved grindability. The dimensions of the wood were reduced in all directions and shrinkage increased with increased treatment temperature and weight loss. With increased treatment temperature, losses of weight and volume increased and bulk density decreased. The low temperature pyrolyzed wood samples improved solid fuel property with high fuel ratio, which are close to lignite/bituminous coal. Morphology of the wood remained intact through the treatment range but the cell walls were thinner. Lastly, these results will improve the understanding of the property changes of the biomass during pretreatment and will help to develop models for process simulation and potential application of the treated biomass.

09 BIOMASS FUELS↗
DOE OSTI2017

Growth Oscillatory Zoning in Erythrite, Ideally Co3(AsO4)2·8H2O: Structural Variations in Vivianite-Group Minerals

The crystal structure of an oscillatory zoned erythrite sample from Aghbar mine, Bou Azzer, Morocco, was refined using synchrotron high-resolution powder X-ray diffraction (HRPXRD) data, Rietveld refinement, space group C2/m, and Z = 2. The crystal contains two sets of oscillatory zones that appear to have developed during epitaxial growth. The unit-cell parameters obtained are a = 10.24799(3) Å, b = 13.42490(7) Å, c = 4.755885(8) Å, β = 105.1116(3)°, and V = 631.680(4) Å3. The empirical formula for erythrite, obtained with electron-probe micro-analysis (EPMA), is [Co2.78Zn0.11Ni0.07Fe0.04]Σ3.00(AsO4)2·8H2O. Erythrite belongs to the vivianite-type structure that contains M1O2(H2O)4 octahedra and M22O6(H2O)4 octahedral dimers that are linked by TO4 (T5+ = As or P) tetrahedra to form complex layers parallel to the (010) plane. These layers are connected by hydrogen bonds. The average [6] = 2.122(1) Å and average [6] = 2.088(1) Å. With space group C2/m, there are two solid solutions: M3(AsO4)2·8H2O and M3(PO4)2·8H2O where M2+ = Mg, Fe, Co, Ni, or Zn. In these As- and P-series, using data from this study and from the literature, we find that their structural parameters evolve linearly with V and in a nearly parallel manner despite of the large difference in size between P5+ (0.170 Å) and As5+ (0.355 Å) cations. Average [4], [6], and [6] distances increase linearly with V. The average distance is affected by M atoms, whereas the average distance is unaffected because it contains shorter and stronger P–O bonds. Although As- and P-series occur naturally, there is no structural reason why similar V-series vivianite-group minerals do not occur naturally or cannot be synthesized.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Circuit-level design principles for transmission-mode microwave impedance microscopy

A recently developed technique of transmission-mode microwave impedance microscopy (T-MIM) has greatly extended the capabilities of standard reflection-mode MIM to novel applications, such as the in operando study of nanoscale electro-acoustic devices. As is common for new techniques, systematic design principles for boosting sensitivity and balancing bandwidth are lacking. Here, we show numerically and analytically that the T-MIM signal is proportional to the reflection-mode voltage enhancement factor η of the circuit, as long as the output impedance of the local voltage source is properly treated. We show that this proportionality holds in the currently achievable “weak sampling” regime and beyond, for which we demonstrate a realistic path with commercially available superconducting components and critically coupled impedance matching networks. Furthermore, we demonstrate that for these next-generation designs, the sensitivity is generally maximized at a slightly different frequency from the unloaded S 11 resonance, which can be explained by the maximum power transfer theorem.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

The Source and Evolutionary History of a Microbial Contaminant Identified Through Soil Metagenomic Analysis

ABSTRACT In this study, strain-resolved metagenomics was used to solve a mystery. A 6.4-Mbp complete closed genome was recovered from a soil metagenome and found to be astonishingly similar to that of Delftia acidovorans SPH-1, which was isolated in Germany a decade ago. It was suspected that this organism was not native to the soil sample because it lacked the diversity that is characteristic of other soil organisms; this suspicion was confirmed when PCR testing failed to detect the bacterium in the original soil samples. D. acidovorans was also identified in 16 previously published metagenomes from multiple environments, but detailed-scale single nucleotide polymorphism analysis grouped these into five distinct clades. All of the strains indicated as contaminants fell into one clade. Fragment length anomalies were identified in paired reads mapping to the contaminant clade genotypes only. This finding was used to establish that the DNA was present in specific size selection reagents used during sequencing. Ultimately, the source of the contaminant was identified as bacterial biofilms growing in tubing. On the basis of direct measurement of the rate of fixation of mutations across the period of time in which contamination was occurring, we estimated the time of separation of the contaminant strain from the genomically sequenced ancestral population within a factor of 2. This research serves as a case study of high-resolution microbial forensics and strain tracking accomplished through metagenomics-based comparative genomics. The specific case reported here is unusual in that the study was conducted in the background of a soil metagenome and the conclusions were confirmed by independent methods. IMPORTANCE It is often important to determine the source of a microbial strain. Examples include tracking a bacterium linked to a disease epidemic, contaminating the food supply, or used in bioterrorism. Strain identification and tracking are generally approached by using cultivation-based or relatively nonspecific gene fingerprinting methods. Genomic methods have the ability to distinguish strains, but this approach typically has been restricted to isolates or relatively low-complexity communities. We demonstrate that strain-resolved metagenomics can be applied to extremely complex soil samples. We genotypically defined a soil-associated bacterium and identified it as a contaminant. By linking together snapshots of the bacterial genome over time, it was possible to estimate how long the contaminant had been diverging from a likely source population. The results are congruent with the derivation of the bacterium from a strain isolated in Germany and sequenced a decade ago and highlight the utility of metagenomics in strain tracking.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Uncertainty quantification of bank vegetation impacts on the flood flow field in the American River, California, using large‐eddy simulations

Bank vegetation plays a key role in both hydrodynamics and morphodynamics of natural rivers; however, these effects are often unaccounted for in the computational flow dynamics of natural waterways. Recent studies using the large‐eddy simulation (LES), however, have attempted to gain insights into the impacts of bank vegetation on the mean flow field of the natural rivers using a vegetation model, which applies a sink term to the momentum equations of motion. This approach accounts for the effects of the vegetation and provides a practical approach to account for the complex patches of bank vegetation in large‐scale rivers. To implement the vegetation model, a drag coefficient reflecting the overall resistance of vegetal structures to the flow is needed, but due to the lack of calibrated data and range of size, density and type of vegetation, this parameter can be a significant source of uncertainty in the model results. Here, in this study, we use uncertainty quantification (UQ) to investigate the hydrodynamics and bed shear results when a bank vegetation is incorporated in an LES model. To this end, we used the polynomial chaos expansion and Monte Carlo sampling techniques to determine the uncertainties associated with the drag coefficient in the vegetation model and from uncertainties in the bed roughness and inflow discharge. The UQ analysis provided spatially varying confidence levels for the spanwise and vertical distribution of velocity magnitude and for the bed shear stress distributions. In addition, Sobol indices were computed to indicate the relative influence that each parameter had on the overall uncertainty. In general, it was found that uncertainty in flow discharge was the dominant source of uncertainty; however, the drag coefficient in the vegetation model and the bed roughness parameter also made significant contribution to the uncertainty near the banks and bed, respectively.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Incorporating geological structure into sensitivity analysis of subsurface contaminant transport

Simulating subsurface contaminant transport at the kilometer-scale often entails modeling reactive flow and transport within and through complex geologic structures. These structures are typically meshed by hand and as a result geologic structure is usually represented by one or a few deterministically generated geological models for uncertainty studies of flow and transport in the subsurface. Uncertainty in geologic structure can have a significant impact on contaminant transport. In this study, the impact of geologic structure on contaminant tracer transport in a shale formation is investigated for a simplified generic deep geologic repository for permanent disposal of spent nuclear fuel. An open-source modeling framework is used to perform a sensitivity analysis study on transport of two tracers from a generic spent nuclear fuel repository with uncertain location of the interfaces between the stratum of the geologic structure. The automated workflow uses sampled realizations of the geological structural model in addition to uncertain flow parameters in a nested sensitivity analysis. Concentration of the tracers at observation points within, in line with, and downstream of the repository are used as the quantities of interest for determining model sensitivity to input parameters and geological realization. Finally, the results of the study indicate that the location of strata interfaces in the geological structure has a first-order impact on tracer transport in the example shale formation, and that this impact may be greater than that of the uncertain flow parameters.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

The moisture outgassing kinetics of a silica reinforced polydimethylsiloxane

We investigated a silica-filled polydimethylsiloxane (PDMS) composite M9787 for potential outgassing in a vacuum/dry environment with the temperature programmed desorption/reaction method. The outgassing kinetics of 463 K vacuum heat-treated samples, vacuum heat-treated samples which were subsequently re-exposed to moisture, and untreated samples were extracted using the isoconversional and constrained iterative regression methods in a complementary fashion. Density functional theory (DFT) calculations of water interactions with a silica surface were also performed to provide insight into the structural motifs leading to the obtained kinetic parameters. Kinetic analysis/model revealed that no outgassing occurs from the vacuum heat-treated samples in subsequent vacuum/dry environment applications at room temperature (~300 K). Moreover, the main effect of re-exposure of the vacuum heat-treated samples to a glove box condition (~30 ppm by volume of H 2 O) for even a couple of days was the formation, on the silica surface fillers, of ~60 ppm by weight of physisorbed and loosely bonded moisture, which subsequently outgasses at room temperature in a vacuum/dry environment in a time span of 10 yr. However, without any vacuum heat treatment and even after 1 h of vacuum pump down, about 300 ppm by weight of H 2 O would be released from the PDMS in the next few hours. Thereafter the outgassing rate slows down substantially. Our presented methodology of using the isoconversional kinetic analysis results and some appropriate nature of the reaction as the constraints for more accurate iterative regression analysis/deconvolution of complex kinetic spectra, and of checking the so-obtained results with first principle calculations such as DFT can serve as a template for treating other complex physical/chemical processes as well.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Application of Linear Additive Conditions for Near-Infrared Diffuse Reflectance Absorption Spectroscopy

Determining the homogeneity of material mixing in real time during product processing is critical for quality control. According to the Kubelka–Munk (K-M) function of diffuse reflectance absorption spectrum, absorbance (A) is approximately linear with the content of the components when the sample scattering coefficient (S) is in a certain range. The S is determined by the particle size of powder samples. Therefore, this study determined particle size ranges that satisfy linear additivity in near-infrared diffuse reflectance spectroscopy (NIRDRS). Thus, the proposed NIRDRS analysis technique can be used to determine the homogeneity of material mixes or analyze the percentages of the components in the mixture. In this study, vitamin B3 and vitamin C were used for preparing mixed samples with varying percentages. The experimental results revealed that linear additivity is satisfied when the powder particle size is in the range of less than 280, 280–450, and 450–900 μm. When the confidence level is 0.01, the actual mixed spectra are not significantly different from the “simulated mixed spectra” constructed by linear addition, with their relative deviations less than 1.08%. The absolute errors of the actual and analytic percentages were within 2.98% for each component in the mixtures. The above conclusions also hold for sorghum, which has a complex material composition. Statistical models cannot analyze the percentages of components in the mixture. In contrast, linear addition and direct calibration approach avoids the use of a large number of samples for statistical modeling and analyze the percentages of mixed samples. Meanwhile, it can be used to discriminate and analyze the material mixing uniformity by building a mechanistic model.

Feng, Zhiyue↗
DOE OSTI2020

Crewmember microbiome may influence microbial composition of ISS habitable surfaces

The International Space Station (ISS) is a complex built environment physically isolated from Earth. Assessing the interplay between the microbial community of the ISS and its crew is important for preventing biomedical and structural complications for long term human spaceflight missions. In this study, we describe one crewmember’s microbial profile from body swabs of mouth, nose, ear, skin and saliva that were collected at eight different time points pre-, during and post-flight. Additionally, environmental surface samples from eight different habitable locations in the ISS were collected from two flights. Environmental samples from one flight were collected by the crewmember and samples from the next flight were collected after the crewmember departed. The microbial composition in both environment and crewmember samples was measured using shotgun metagenomic sequencing and processed using the Livermore Metagenomics Analysis Toolkit. Ordination of sample to sample distances showed that of the eight crew body sites analyzed, skin, nostril, and ear samples are more similar in microbial composition to the ISS surfaces than mouth and saliva samples; and that the microbial composition of the crewmember’s skin samples are more closely related to the ISS surface samples collected by the crewmember on the same flight than ISS surface samples collected by other crewmembers on different flights. In these collections, species alpha diversity in saliva samples appears to decrease during flight and rebound after returning to Earth. This is the first study to compare the ISS microbiome to a crewmember’s microbiome via shotgun metagenomic sequencing. We observed that the microbiome of the surfaces inside the ISS resemble those of the crew’s skin. These data support future crew and ISS microbial surveillance efforts and the design of preventive measures to maintain crew habitat onboard spacecraft destined for long term space travel.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Establishing Isotopic Measurement Capabilities using Laser-Induced Breakdown Spectroscopy for the Molten Salt Reactor Campaign

Proof-of-principle H isotope ratios of aqueous aerosol systems and liquid droplets on filter paper have been measured using laser-induced breakdown spectroscopy (LIBS) with root mean square error of prediction values down to 1.9%. Molten salt reactors (MSRs) will consist of a complex chemical and radiological system consistently producing new fission products as the reactor operates. Some of these fission products and/or their daughter species will leave the salt in the reactor off-gas. Monitoring the composition of the off-gas, as well as the salt itself, is important for monitoring reactor performance, including burnup, corrosion, and the concentration of impurities. Tritium is of concern for MSRs because it will be produced from the irradiation of key salt constituents, including Li and Be. LIBS offers an avenue for in situ salt and off-gas monitoring by firing a laser onto or into the sample stream to generate a plasma. The plasma light can be monitored to measure an elemental fingerprint of the sample. Extending this analysis to include isotopic ratios offers a critical expansion of the in situ monitoring capabilities being developed. This study demonstrates the expansion of Oak Ridge National Laboratory’s LIBS capabilities to monitor isotopes and shows how simple calibrations may provide rapid semiquantitative models.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2016

Custom fabrication of biomass containment devices using 3-D printing enables bacterial growth analyses with complex insoluble substrates

Physiological studies of recalcitrant polysaccharide degradation are challenging for several reasons, one of which is the difficulty in obtaining a reproducibly accurate real-time measurement of bacterial growth using insoluble substrates. Current methods suffer from several problems including (i) high background noise due to the insoluble material interspersed with cells, (ii) high consumable and reagent cost and (iii) significant time delay between sampling and data acquisition. A customizable substrate and cell separation device would provide an option to study bacterial growth using optical density measurements. To test this hypothesis we used 3-D printing to create biomass containment devices that allow interaction between insoluble substrates and microbial cells but do not interfere with spectrophotometer measurements. Evaluation of materials available for 3-D printing indicated that UV-cured acrylic plastic was the best material, being superior to nylon or stainless steel when examined for heat tolerance, reactivity, and ability to be sterilized. Cost analysis of the 3-D printed devices indicated they are a competitive way to quantitate bacterial growth compared to viable cell counting or protein measurements, and experimental conditions were scalable over a 100-fold range. The presence of the devices did not alter growth phenotypes when using either soluble substrates or insoluble substrates. Furthermore, we applied biomass containment to characterize growth of Cellvibrio japonicus on authentic lignocellulose (non-pretreated corn stover), and found physiological evidence that xylan is a significant nutritional source despite an abundance of cellulose present.

3-D printing↗
DOE OSTI2026

Understanding polaronic transport in complex oxides by combining precise synthesis and first-principles many-body theory

In complex oxides, charge carriers often couple strongly with lattice vibrations to form polarons–entangled electron–phonon quasiparticles whose transport properties remain difficult to characterize. Experimental access to intrinsic polaronic transport requires ultraclean samples, while theoretical description demands methods beyond low-order perturbation theory. Here, we show a predictive theory–experiment workflow to study polaron transport in complex oxides. Focusing on a prototypical polaronic oxide, anatase TiO 2 , we combine growth of high-quality oxygen-vacancy-doped films using hybrid molecular beam epitaxy with a first-principles electron–phonon diagrammatic Monte-Carlo (FEP-DMC) framework recently developed for accurate polaron predictions. Our films exhibit record-high electron mobility for anatase TiO 2 , in excellent agreement with FEP-DMC calculations conducted prior to experiment, which predict a room-temperature mobility of 45 ± 15 cm −2 V −1 s −1 and a mobility-temperature scaling of μ ∝ T −1.9 ± 0.077 . Microscopic analysis using scanning transmission electron microscopy and x-ray photoelectron spectroscopy reveals the role of oxygen vacancies in modulating transport at lower temperatures. FEP-DMC further provides quantitative insight into polaron formation energy, phonon cloud distribution, lattice distortion around the polaron, and the polaronic contribution to mobility. Together, these results provide a deeper microscopic understanding of large-polaron transport in a complex oxide and provide the blueprint to characterize other polaronic materials.

anatase TiO2↗
DOE OSTI2025

Studying Aerosol, Clouds, and Air Quality in the Coastal Urban Environment of Southeastern Texas

A multi-agency succession of field campaigns was conducted in southeastern Texas during July 2021 through October 2022 to study the complex interactions of aerosols, clouds and air pollution in the coastal urban environment. As part of the Tracking Aerosol Convection interactions Experiment (TRACER), the TRACER- Air Quality (TAQ) campaign the Experiment of Sea Breeze Convection, Aerosols, Precipitation and Environment (ESCAPE) and the Convective Cloud Urban Boundary Layer Experiment (CUBE), a combination of ground-based supersites and mobile laboratories, shipborne measurements and aircraft-based instrumentation were deployed. These diverse platforms collected high-resolution data to characterize the aerosol microphysics and chemistry, cloud and precipitation micro- and macro-physical properties, environmental thermodynamics and air quality-relevant constituents that are being used in follow-on analysis and modeling activities. We present the overall deployment setups, a summary of the campaign conditions and a sampling of early research results related to: (a) aerosol precursors in the urban environment, (b) influences of local meteorology on air pollution, (c) detailed observations of the sea breeze circulation, (d) retrieved supersaturation in convective updrafts, (e) characterizing the convective updraft lifecycle, (f) variability in lightning characteristics of convective storms and (g) urban influences on surface energy fluxes. The work concludes with discussion of future research activities highlighted by the TRACER model-intercomparison project to explore the representation of aerosol-convective interactions in high-resolution simulations.

54 ENVIRONMENTAL SCIENCES↗