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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 OSTI2021

Hierarchical Nanomaterials Assembled from Peptoids and Other Sequence-Defined Synthetic Polymers

In nature, the self-assembly of sequence-specific biopolymers into hierarchical structures plays an essential role in the construction of functional biomaterials. To develop synthetic materials that can mimic and surpass the function of these natural counterparts, various sequence-defined bio- and biomimetic polymers have been developed and exploited as building blocks for hierarchical self-assembly. This review summarizes the recent advances in the molecular self-assembly of hierarchical nanomaterials based on peptoids (or poly-N-substituted glycines) and other sequence-defined synthetic polymers. Modern techniques to monitor the assembly mechanisms and characterize the physicochemical properties of these self-assembly systems are highlighted. In addition, discussions about their potential applications in biomedical sciences and renewable energy are also included. Furthermore, this review aims to highlight essential features of sequence-defined synthetic polymers (e.g., high stability and protein-like high-information content) and how these unique features enable the construction of robust biomimetic functional materials with high programmability and predictability, with an emphasis on peptoids and their self-assembled nanomaterials.

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

Bayesian Optimization of Non-Invariant Systems with Constraints Developed for Application to the ECR Ion Source VENUS

In this work, we consider the optimization of non-invariant systems with both safety and control constraints. We present a new approach based on Bayesian optimization for the dynamic, safe and controlled optimization of such systems. Although there are other possible use cases, we focus on the application to the electron cyclotron resonance ion source VENUS. From experimental data, we have observed that VENUS behaves to first order as a non-invariant dynamic system with moving areas of instability. Our novel approach aims at providing a tool that can maintain system optimization in a safe way. This is accomplished by making sure the objective function, the beam current in the case of VENUS, does not fall under an operational minimum, while simultaneously requiring the optimization to avoid areas where VENUS is unstable. We compare the result of our approach on synthetic data modeled to mimic the behavior of VENUS with two methods from the literature, a standard Bayesian optimizer and a safe Bayesian optimizer, both adapted to deal with dynamic systems. A cross Student T-test is conducted to show the significance of the improvement given by the new method we introduce here, regarding the two preexisting methods we compared to. The results of the tests conducted on synthetic data show that the proposed method succeeds at maintaining the system optimized and obeys the predefined constraints better than the literature methods explored.

Bayesian optimization↗
DOE OSTI2025

MIC-DP: A Scalable Correlation-Aware Differential Privacy Framework for High-Dimensional Data

Conventional differential privacy (DP) assumes record independence, limiting effectiveness on real-world datasets with temporal, spatial, or structural correlations. These dependencies undermine privacy guarantees and degrade utility in domains like healthcare, IoT, and smart city analytics. We propose Maximum Information Correlated Differential Privacy (MIC-DP), a novel framework that dynamically calibrates noise based on statistical dependencies. MIC-DP uses the Maximum Information Coefficient (MIC) to capture both linear and nonlinear correlations without explicit modeling, enabling adaptive sensitivity adjustment and improved privacy–utility trade-offs. Evaluations on healthcare (MIMIC), demographic (ACI), and synthetic datasets show that MIC-DP reduces mean absolute error (MAE) by up to 5.2% under strict privacy budgets (ϵ≤1), with aggregate utility improvements reaching 18% across datasets and evaluation metrics. MIC-DP provides formal (ϵ,δ)-privacy guarantees, scales efficiently with feature count, and supports deployment in moderate-scale, privacy-sensitive applications. Its tunable performance and runtime efficiency make MIC-DP suitable for privacy-sensitive applications where low-latency analytics and strong privacy guarantees must coexist. These results demonstrate MIC-DP’s effectiveness as a correlation-aware solution for practical DP.

Yang, Wenjun [Univ. of Washington, Tacoma, WA (Uni↗
DOE OSTI2023

Macrocyclic β‐Sheets Stabilized by Hydrogen Bond Surrogates

Abstract Mimics of protein secondary and tertiary structure offer rationally‐designed inhibitors of biomolecular interactions. β‐Sheet mimics have a storied history in bioorganic chemistry and are typically designed with synthetic or natural turn segments. We hypothesized that replacement of terminal inter‐β‐strand hydrogen bonds with hydrogen bond surrogates (HBS) may lead to conformationally‐defined macrocyclic β‐sheets without the requirement for natural or synthetic β‐turns, thereby providing a minimal mimic of a protein β‐sheet. To access turn‐less antiparallel β‐sheet mimics, we developed a facile solid phase synthesis protocol. We surveyed a dataset of protein β‐sheets for naturally observed interstrand side chain interactions. This bioinformatics survey highlighted an over‐abundance of aromatic–aromatic, cation‐π and ionic interactions in β‐sheets. In correspondence with natural β‐sheets, we find that minimal HBS mimics show robust β‐sheet formation when specific amino acid residue pairings are incorporated. In isolated β‐sheets, aromatic interactions endow superior conformational stability over ionic or cation‐π interactions. Circular dichroism and NMR spectroscopies, along with high‐resolution X‐ray crystallography, support our design principles.

Chemistry↗
DOE OSTI2022

Utilization of lignocellulosic biofuel conversion residue by diverse microorganisms

Lignocellulosic conversion residue (LCR) is the material remaining after deconstructed lignocellulosic biomass is subjected to microbial fermentation and treated to remove the biofuel. Technoeconomic analyses of biofuel refineries have shown that further microbial processing of this LCR into other bioproducts may help offset the costs of biofuel generation. Identifying organisms able to metabolize LCR is an important first step for harnessing the full chemical and economic potential of this material. In this study, we investigated the aerobic LCR utilization capabilities of 71 Streptomyces and 163 yeast species that could be engineered to produce valuable bioproducts. The LCR utilization by these individual microbes was compared to that of an aerobic mixed microbial consortium derived from a wastewater treatment plant as representative of a consortium with the highest potential for degrading the LCR components and a source of genetic material for future engineering efforts. We analyzed several batches of a model LCR by chemical oxygen demand (COD) and chromatography-based assays and determined that the major components of LCR were oligomeric and monomeric sugars and other organic compounds. Many of the Streptomyces and yeast species tested were able to grow in LCR, with some individual microbes capable of utilizing over 40% of the soluble COD. For comparison, the maximum total soluble COD utilized by the mixed microbial consortium was about 70%. This represents an upper limit on how much of the LCR could be valorized by engineered Streptomyces or yeasts into bioproducts. To investigate the utilization of specific components in LCR and have a defined media for future experiments, we developed a synthetic conversion residue (SynCR) to mimic our model LCR and used it to show lignocellulose-derived inhibitors (LDIs) had little effect on the ability of the Streptomyces species to metabolize SynCR. We found that LCR is rich in carbon sources for microbial utilization and has vitamins, minerals, amino acids and other trace metabolites necessary to support growth. Testing diverse collections of Streptomyces and yeast species confirmed that these microorganisms were capable of growth on LCR and revealed a phylogenetic correlation between those able to best utilize LCR. Identification and quantification of the components of LCR enabled us to develop a synthetic LCR (SynCR) that will be a useful tool for examining how individual components of LCR contribute to microbial growth and as a substrate for future engineering efforts to use these microorganisms to generate valuable bioproducts.

09 BIOMASS FUELS↗
DOE OSTI2020

Development and Validation of Quantitative Model-Based Image Reconstruction for NDE of Reinforced Steel-Lined Concrete Structures: Kal-El FY 2020

This project studied the capabilities of Model-Based Image Reconstruction (MBIR) and Machine Learning (ML) algorithms in the imaging and estimation of rebar corrosion from ultrasound signals. The application was challenging due to the introduction of a steel liner between the sensor and the concrete containing the rebar. The study focused in a synthetic specimen with a 6.35 mm thick steel liner, and a 19.05 mm diameter rebar at a depth of 44.5 mm and with four levels of corrosion; 0%, 20%, 50%, and 100% corrosion level. The corrosion was applied uniformly around the rebar, generating a ring in the perimeter of the rebar with different acoustic density. In order to generate a realistic synthetic dataset, we added random texture to the concrete of the synthetic specimens. This texture will mimic the variations encountered in real concrete specimens.We adapted our MBIR algorithm for the application and enhanced the algorithm to integrate in the physical model known specimen features, such as the steel liner thickness. The new MBIR method was able to cancel out reverberation from the steel liner and properly image the rebar. In particular, corrosion for the 50% and 100% cases were easily visible and quantitative metrics showed a slight separation for the 0% and 20% levels. The quantitative results were in agreement with the qualitative assessment. We also developed a ML XGBoost model to estimate corrosion level from the ultrasound signals. By combining the ML method with MBIR, we can pinpoint in the ultrasound signals the section that corresponds to the echoes from the rebar. The extract signals are processed by the XGBoost model for prediction. From each system scan, we obtain 15 predictions. The median prediction value is used as the final prediction. The True Acceptance Rate for the method is over 99%.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Dynamic self-assembly of compartmentalized DNA nanotubes

Abstract Bottom-up synthetic biology aims to engineer artificial cells capable of responsive behaviors by using a minimal set of molecular components. An important challenge toward this goal is the development of programmable biomaterials that can provide active spatial organization in cell-sized compartments. Here, we demonstrate the dynamic self-assembly of nucleic acid (NA) nanotubes inside water-in-oil droplets. We develop methods to encapsulate and assemble different types of DNA nanotubes from programmable DNA monomers, and demonstrate temporal control of assembly via designed pathways of RNA production and degradation. We examine the dynamic response of encapsulated nanotube assembly and disassembly with the support of statistical analysis of droplet images. Our study provides a toolkit of methods and components to build increasingly complex and functional NA materials to mimic life-like functions in synthetic cells.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Early-Stage Aggregation and Crystalline Interactions of Peptoid Nanomembranes

Fully synthetic peptoid membranes are known to mimic important features of biological membranes, with several advantages over other biomimetic membranes. A fundamental understanding of how the individual peptoid amphiphiles assemble in solution to form the bilayer membrane is key to unlocking their versatility for application in a broad range of processes. Here, in this study, in situ X-ray scattering and molecular dynamics simulations are used to understand the early stages of assembly of three different peptoids that exhibit distinctly different crystallization kinetics. The in situ measurements reveal that the peptoids aggregate first into a nascent phase that is less crystalline than the assembled peptoid membrane. Anisotropic aromatic interactions are determined to be the dominant driving force in the early stages of membrane formation. These results provide key insights into how the peptoid assembly may be manipulated during the early stages of assembly and nucleation and growth.

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

Leveraging BERT and Network-Based Attention Analysis for Identifying Treatment Milestones in EHRs

This study introduces a sophisticated data-driven framework for analyzing Electronic Health Records (EHRs) using transformer-based models to identify and disentangle overlapping treatment contexts. The framework leverages a preprocessing pipeline that transforms structured procedural codes into semantically enriched descriptive text, enabling the use of attention mechanisms to cluster medical events into treatment milestones—cohesive and distinct components of care processes. The methodology is rigorously validated using synthetic datasets derived from the MIMIC-III database, designed to simulate the heterogeneity and overlapping procedural contexts characteristic of real-world EHR scenarios. Quantitative evaluation highlights the framework’s robustness in disentangling concurrent care pathways, with attention metrics and unsupervised clustering approaches demonstrating the ability to preserve intra-context relationships while distinguishing inter-context dependencies. By addressing challenges inherent in data heterogeneity, this approach provides a foundation for uncovering complex treatment patterns, advancing clinical decision-making, and optimizing resource allocation in diverse healthcare environments.

Kim, Minsu [ORNL] (ORCID:0000000224185535)↗
DOE OSTI2023

Reactive high-spin iron(IV)-oxo sites through dioxygen activation in a metal–organic framework

In nature, nonheme iron enzymes use dioxygen to generate high-spin iron(IV)=O species for a variety of oxygenation reactions. Although synthetic chemists have long sought to mimic this reactivity, the enzyme-like activation of O 2 to form high-spin iron(IV) = O species remains an unrealized goal. Here, we report a metal–organic framework featuring iron(II) sites with a local structure similar to that in α-ketoglutarate-dependent dioxygenases. The framework reacts with O 2 at low temperatures to form high-spin iron(IV) = O species that are characterized using in situ diffuse reflectance infrared Fourier transform, in situ and variable-field Mössbauer, Fe Kβ x-ray emission, and nuclear resonance vibrational spectroscopies. In the presence of O 2 , the framework is competent for catalytic oxygenation of cyclohexane and the stoichiometric conversion of ethane to ethanol.

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

Bobfinchite, Na[(UO2)8O3(OH)11]·10H2O, a new Na-bearing member of the schoepite family

Abstract The new mineral bobfinchite (IMA2020-082), Na[(UO2)8O3(OH)11]·10H2O, was found in the Burro mine, Slick Rock district, San Miguel County, Colorado, U.S.A., where it occurs as an oxidation product of uraninite on asphaltite matrix in intimate association with gypsum, natrozippeite, metaschoepite, and uranopilite. Bobfinchite crystals are transparent to translucent, yellow, lozenge-shaped disks up to 0.3 mm wide. Crystals are flattened on [100] and exhibit the forms {100}, {011}, {021}, {021}, and {011}. Bobfinchite has a pale-yellow streak and emits very dim yellow fluorescence under 365 nm ultraviolet illumination. The crystals are brittle with very good {100} cleavage and irregular, stepped fracture. The Mohs hardness is ca. 2 based on scratch tests. The calculated density is 5.044 g/cm3 based on the empirical formula and 5.036 g/cm3 for the ideal formula. Bobfinchite is optically biaxial (–), with α = 1.690(5), β = 1.7205(5), and γ = 1.730(5) (white light). The measured 2V, estimated from the interference figure, is 55(5)° and the calculated value is 59.1°. Dispersion is moderate, r > v; orientation: X = a, Y = b, Z = c; pleochroism: X nearly colorless, Y yellow, Z yellow; X < Y ≈Z. Electron microprobe analysis provided the empirical formula (Na0.99Pb0.02)[(UO2)7.99O3(OH)11]·10H2O. The five strongest X-ray powder diffraction lines are [dobs in Å(I)(hkl)]: 7.34(100)(200), 3.59(50)(024), 3.23(60)(224), 3.18(36)(240), and 2.01(23)(624,551,208,640,346). Bobfinchite is orthorhombic, Pbcn, a = 14.6249(9), b = 14.0389(10), c = 16.6923(10) Å, V = 3427.2(4) Å3, and Z = 4. The structure of bobfinchite (R1 = 0.0330 for 3770 I > 4σI) is built from uranyl oxide-hydroxide sheets that adopt the fourmarierite topology, with interlayer Na+ and H2O groups. Both the sheet and interlayer topology mimic those observed in natural and synthetic Na-metaschoepites studied previously, and as seen in other uranyl oxide hydrate minerals, charge balance is achieved at specific sites in the sheet through the substitution O2– ↔ (OH)–.

Geochemistry & Geophysics↗
DOE OSTI2024

Cu site differentiation in tetracopper(I) sulfide clusters enables biomimetic N 2 O reduction

Copper clusters feature prominently in both metalloenzymes and synthetic nanoclusters that mediate catalytic redox transformations of gaseous small molecules. Such reactions are critical to biological energy conversion and are expected to be crucial parts of renewable energy economies. However, the precise roles of individual metal atoms within clusters are difficult to elucidate, particularly for cluster systems that are dynamic under operating conditions. Here, we present a metal site-specific analysis of synthetic Cu 4 (μ 4 -S) clusters that mimic the Cu Z active site of the nitrous oxide reductase enzyme. Leveraging the ability to obtain structural snapshots of both inactive and active forms of the synthetic model system, we analyzed both states using resonant X-ray diffraction anomalous fine structure (DAFS), a technique that enables X-ray absorption profiles of individual metal sites within a cluster to be extracted independently. Using DAFS, we found that a change in cluster geometry between the inactive and active states is correlated to Cu site differentiation that is presumably required for efficient activation of N 2 O gas. More precisely, we hypothesize that the Cu δ+ ∙∙∙Cu δ- pairs produced upon site differentiation are poised for N 2 O activation, as supported by computational modeling. These results provide an unprecedented level of detail on the roles of individual metal sites within the synthetic cluster system and how those roles interplay with cluster geometry to impact the reactivity function. We expect this fundamental knowledge to inform understanding of metal clusters in settings ranging from (bio)molecular to nanocluster to extended solid systems involved in energy conversion.

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

Biomimetic Rebuilding of Multifunctional Red Blood Cells: Modular Design Using Functional Components

The design and synthesis of artificial materials that mimic the structures, mechanical properties, and ultimately functionalities of biological cells remains a current holy grail of materials science. Here based on a silica cell bio-replication approach, we report the design and construction of synthetic rebuilt red blood cells (RRBCs) that fully mimic the broad properties of native RBCs: size, biconcave shape, deformability, oxygen carrying capacity, long circulation time. Four successive nano-scale processing steps: RBC bioreplication, layer-by-layer polymer deposition, and precision silica etching, followed by RBC ghost membrane vesicles fusion are employed for RRBC construction. A panel of physicochemical analyses including zeta potential measurement, fluorescence microscopy, and antibody-mediated agglutination assay proved the recapitulation of RBC shape, size, and membrane structure. Flow-based deformation studies carried out in a microfluidic blood capillary model confirrned the ability of RRBCs to deform and pass through small slits and reconstitute themselves in a manner comparable to native RBCs. Circulation studies of RRBCs conducted ex-ovo in a chick embryo and in vivo in a mouse model demonstrated the requirement of both deformability and native cell membrane surface to achieve long-term circulation. To confer additional non-native functionalities to RRBCs, we developed modular procedures in which to load functional cargos such as hemoglobin, drugs, magnetic nanoparticles, and ATP biosensors within the RRBC interior to enable various functions, including oxygen delivery, therapeutic drug delivery, magnetic manipulation, and toxin biosensing and detection. Taken together, RRBCs represent a class of long circulating RBC-inspired artificial hybrid materials with a broad range of potential applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Lipid sponge droplets as programmable synthetic organelles

Living cells segregate molecules and reactions in various subcellular compartments known as organelles. Spatial organization is likely essential for expanding the biochemical functions of synthetic reaction systems, including artificial cells. Many studies have attempted to mimic organelle functions using lamellar membrane-bound vesicles. However, vesicles typically suffer from highly limited transport across the membranes and an inability to mimic the dense membrane networks typically found in organelles such as the endoplasmic reticulum. Here, we describe programmable synthetic organelles based on highly stable nonlamellar sponge phase droplets that spontaneously assemble from a single-chain galactolipid and nonionic detergents. Due to their nanoporous structure, lipid sponge droplets readily exchange materials with the surrounding environment. In addition, the sponge phase contains a dense network of lipid bilayers and nanometric aqueous channels, which allows different classes of molecules to partition based on their size, polarity, and specific binding motifs. The sequestration of biologically relevant macromolecules can be programmed by the addition of suitably functionalized amphiphiles to the droplets. We demonstrate that droplets can harbor functional soluble and transmembrane proteins, allowing for the colocalization and concentration of enzymes and substrates to enhance reaction rates. Droplets protect bound proteins from proteases, and these interactions can be engineered to be reversible and optically controlled. Our results show that lipid sponge droplets permit the facile integration of membrane-rich environments and self-assembling spatial organization with biochemical reaction systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

The Kimberlina synthetic multiphysics dataset for CO 2 monitoring investigations

Abstract We present a synthetic multi‐scale, multi‐physics dataset constructed from the Kimberlina 1.2 CO 2 reservoir model based on a potential CO 2 storage site in the Southern San Joaquin Basin of California. Among 300 models, one selected reservoir‐simulation scenario produces hydrologic‐state models at the onset and after 20 years of CO 2 injection. Subsequently, these models were transformed into geophysical properties, including P‐ and S‐wave seismic velocities, saturated density where the saturating fluid can be a combination of brine and supercritical CO 2 , and electrical resistivity using established empirical petrophysical relationships. From these 3D distributions of geophysical properties, we have generated synthetic time‐lapse seismic, gravity and electromagnetic responses with acquisition geometries that mimic realistic monitoring surveys and are achievable in actual field situations. We have also created a series of synthetic well logs of CO 2 saturation, acoustic velocity, density and induction resistivity in the injection well and three monitoring wells. These were constructed by combining the low‐frequency trend of the geophysical models with the high‐frequency variations of actual well logs collected at the potential storage site. In addition, to better calibrate our datasets, measurements of permeability and pore connectivity have been made on cores of Vedder Sandstone, which forms the primary reservoir unit. These measurements provide the range of scales in the otherwise synthetic dataset to be as close to a real‐world situation as possible. This dataset consisting of the reservoir models, geophysical models, simulated time‐lapse geophysical responses and well logs forms a multi‐scale, multi‐physics testbed for designing and testing geophysical CO 2 monitoring systems as well as for imaging and characterization algorithms. The suite of numerical models and data have been made publicly available for downloading on the National Energy Technology Laboratory's (NETL) Energy Data Exchange (EDX) website.

58 GEOSCIENCES↗
DOE OSTI2023

SYNCA: A Synthetic Cyclotron Antenna for the Project 8 Collaboration

Cyclotron Radiation Emission Spectroscopy (CRES) is a technique for measuring the kinetic energy of charged particles through a precision measurement of the frequency of the cyclotron radiation generated by the particle's motion in a magnetic field. The Project 8 collaboration is developing a next-generation neutrino mass measurement experiment based on CRES. One approach is to use a phased antenna array, which surrounds a volume of tritium gas, to detect and measure the cyclotron radiation of the resulting β-decay electrons. To validate the feasibility of this method, Project 8 has designed a test stand to benchmark the performance of an antenna array at reconstructing signals that mimic those of genuine CRES events. To generate synthetic CRES events, a novel probe antenna has been developed, which emits radiation with characteristics similar to the cyclotron radiation produced by charged particles in magnetic fields. This paper outlines the design, construction, and characterization of this Synthetic Cyclotron Antenna (SYNCA). Furthermore, we perform a series of measurements that use the SYNCA to test the position reconstruction capabilities of the digital beamforming reconstruction technique. Finally, we find that the SYNCA produces radiation with characteristics closely matching those expected for cyclotron radiation and reproduces experimentally the phenomenology of digital beamforming simulations of true CRES signals.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Water, Solute, and Ion Transport in De Novo-Designed Membrane Protein Channels

Biological organisms engineer peptide sequences to fold into membrane pore proteins capable of performing a wide variety of transport functions. Synthetic de novo-designed membrane pores can mimic this approach to achieve a potentially even larger set of functions. Here, in this work, we explore water, solute, and ion transport in three de novo designed β-barrel membrane channels in the 5–10 Å pore size range. We show that these proteins form passive membrane pores with high water transport efficiencies and size rejection characteristics consistent with the pore size encoded in the protein structure. Ion conductance and ion selectivity measurements also show trends consistent with the pore size, with the two larger pores showing weak cation selectivity. MD simulations of water and ion transport and solute size exclusion are consistent with the experimental trends and provide further insights into structure–function correlations in these membrane pores.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Probabilistic estimation of depth-resolved profiles of soil thermal diffusivity from temperature time series: Supporting Data

This dataset consists of soil temperature time series that were used to estimate soil thermal diffusivity and its uncertainty trough the probabilistic modelling approach developed and presented in the article named "Probabilistic estimation of depth-resolved profiles of soil thermal diffusivity from temperature time series" and published in Earth Surface Dynamics. There are two compressed (.zip) files that contains synthetic (Synthetic_soiltemp_Teller.zip) and field (Field_soiltemp_Teller.zip) data. There is one MATLAB file that requires MATLAB to execute but any text editor can open it. The Synthetic_soiltemp_Teller.zip file includes 5 comma-delimited data files (.csv) each of which contains soil temperature time series generated through forward modeling (i.e., heat-conduction process in a heterogeneous medium using an explicit finite difference method) to mimic various types of temperature gradients, trend and fluctuations. These synthetic soil temperatures were used to investigate the impact of different environmental conditions on the uncertainty of thermal diffusivity estimates. The Field_soiltemp_Teller.zip file contains 28 comma-delimited data files (.csv) out of which (a) 27 files includes soil temperature time series recorded from 27 temperature probes located in a site along Teller Road about 40 km northwest of Nome, Alaska (64.72°N, 165.94°W), (b) one includes the name and coordinates of the 27 probes. These field soil temperatures were used to infer soil thermal diffusivity at numerous locations and depths in a discontinuous permafrost environment, and to evaluate the links between the estimated soil thermal diffusivity values and soil physical properties. The comma-delimited data files (.csv) of the synthetic and field soil temperature time series includes date and time (UTC) in the first column and soil temperature from 5 cm below the ground surface to 1.05 m depth (with 5 or 10 cm spacing between sensors) in the other columns. The measurements were acquired every 15 minutes. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗