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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 181 records · Page 10

From Structure to Functions: Metagenomics-Enabled Predictive Understanding of Soil Microbial Feedbacks to Climate Change

Understanding the responses, adaptations and feedback mechanisms of biological communities to climate change is critical to project future states of earth and climate systems. Although a significant amount of knowledge is available on the feedbacks of aboveground communities to climate change, the responses of belowground microbial communities are still poorly understood. This is due to challenges in analyzing soil microbial communities in terms of their diversity, structure and function. Thus, the ultimate goal of this study is to advance system-level predictive understanding of the feedbacks of belowground microbial communities to multiple climate change factors and their impacts on soil carbon (C) cycling processes. For this, cutting-edge integrated metagenomic technologies are employed to establish mechanistic linkages among aboveground plant communities, belowground microbial communities, ecosystem processes and functions and climate change. Towards this goal, the following four specific objectives are pursued: (i) To determine the responses of microbial community structure, functions and activities to climate warming, altered precipitation, soil moisture regime and/or clipping in the tundra and temperate grassland ecosystems; (ii) To determine the temperature sensitivity and the effect of substrate priming on recalcitrant C decomposition; (iii) To determine microbiological bases underlying temperature sensitivity of recalcitrant C decomposition; and (iv) To develop integrated bioinformatics and modeling approaches to scale information across different organizational levels towards predictive understanding of ecosystem responses to multiple climate change factors in collaboration with the Knowledge Base (KBase) and integrated into their database. Warming experiments in an Alaskan tundra permafrost soil (AK) as well as an Oklahoma temperate grassland soil (OK) provide a more complete picture of the effects of warming on belowground microbial communities of different (key) soil ecosystems. Numerous research activities have been carried out by the institutions under the support of this program. For brevity, a few key results and their significance are highlighted in this report.

54 ENVIRONMENTAL SCIENCES↗

Updated Rice Kinase Database RKD 2.0: enabling transcriptome and functional analysis of rice kinase genes

Protein kinases catalyze the transfer of a phosphate moiety from a phosphate donor to the substrate molecule, thus playing critical roles in cell signaling and metabolism. Although plant genomes contain more than 1000 genes that encode kinases, knowledge is limited about the function of each of these kinases. A major obstacle that hinders progress towards kinase characterization is functional redundancy. To address this challenge, we previously developed the rice kinase database (RKD) that integrated omics-scale data within a phylogenetics context.

Agriculture↗

Enabling URR Self Shielding Functionality in SAMMY [Slides]

This lecture is on enabling Unresolved Resonance Energy Range (URR) self-shielding functionality in SAMMY. This presentation covers Fiscal Year 2022 milestones, and motivations driving this endeavor. This presentation includes slides depicting the current self-shielding correction workflow. Additionally, this presentation includes a look into the doppler broadening issue and the verification of capture. This lecture concludes with envisioned future work.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Sensory stimulation for upper limb amputations modulates adaptability of cortical large-scale systems and combination of somatosensory and visual inputs

Abstract Touch-like phantom limb sensations can be elicited through targeted transcutaneous electrical nerve stimulation (tTENS) in individuals with upper limb amputation. The corresponding impact of sensory stimulation on cortical activity remains an open question. Brain network research shows that sensorimotor cortical activity is supported by dynamic changes in functional connections between relevant brain regions. These groups of interconnected regions are functional modules whose architecture enables specialized function and related neural processing supporting individual task needs. Using electroencephalographic (EEG) signals to analyze modular functional connectivity, we investigated changes in the modular architecture of cortical large-scale systems when participants with upper limb amputations performed phantom hand movements before, during, and after they received tTENS. We discovered that tTENS substantially decreased the flexibility of the default mode network (DMN). Furthermore, we found increased interconnectivity (measured by a graph theoretic integration metric) between the DMN, the somatomotor network (SMN) and the visual network (VN) in the individual with extensive tTENS experience. While for individuals with less tTENS experience, we found increased integration between DMN and the attention network. Our results provide insights into how sensory stimulation promotes cortical processing of combined somatosensory and visual inputs and help develop future tools to evaluate sensory combination for individuals with amputations.

60 APPLIED LIFE SCIENCES↗

New Density Functional Theory Approaches for Enabling Prediction of Chemical and Physical Properties of Plutonium and Other Actinides

Density Functional Theory (DFT) based Equation of State (EOS) construction is a prominent part of Sandia's capabilities to support engineering sciences. This capability is based on amending experimental data with information gained from computational investigations, in parts of the phase space where experimental data is hard, dangerous, or expensive to obtain. A prominent materials area where such computational investigations are hard to perform today because of limited accuracy is actinide and lanthanide materials. The Science of Extreme Environment Lab Directed Research and Development project described in this Report has had the aim to cure this accuracy problem. We have focused on the two major factors which would allow for accurate computational investigations of actinide and lanthanide materials: (1) The fully relativistic treatment needed for materials containing heavy atoms, and (2) the needed improved performance of DFT exchange-correlation functionals. We have implemented a fully relativistic treatment based on the Dirac Equation into the LANL code RSPt and we have shown that such a treatment is imperative when calculating properties of materials containing actinides and/or lanthanides. The present standard treatment that only includes some of the relativistic terms is not accurate enough and can even give misleading results. Compared to calculations previously considered state of the art, the Dirac treatment gives a substantial change in equilibrium volume predictions for materials with large spin-orbit coupling. For actinide and lanthanide materials, a Dirac treatment is thus a fundamental requirement in any computational investigation, including those for DFT-based EOS construction. For a full capability, a DFT functional capable of describing strongly correlated systems such as actinide materials need to be developed. Using the previously successful subsystem functional scheme developed by Mattsson et.al., we have created such a functional. In this functional the Harmonic Oscillator Gas is providing the necessary reference system for the strong correlation and localization occurring in actinides. Preliminary testing shows that the new Hao-Armiento-Mattsson (HAM) functional gives a trend towards improved results for the crystalline copper oxide test system we have chosen. This test system exhibits the same exchange-correlation physics as the actinide systems do, but without the relativistic effects, giving access to a pure testing ground for functionals. During the work important insights have been gained. An example is that currently available functionals, contrary to common belief, make large errors in so called hybridization regions where electrons from different ions interact and form new states. Together with the new understanding of functional issues, the Dirac implementation into the RSPt code will permit us to gain more fundamental understanding, both quantitatively and qualitatively, of materials of importance for Sandia and the rest of the Nuclear Weapons complex.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Functionalized Graphene via a One-Pot Reaction Enabling Exact Pore Sizes, Modifiable Pore Functionalization, and Precision Doping

Functionalizing graphene with exact pore size, specific functional groups, and precision doping poses many significant challenges. Current methods lack precision and produce random pore sizes, sites of attachment, and amounts of dopant, leading to compromised structural integrity and affecting graphene’s applications. In this work, we report a strategy for the synthesis of functionalized graphitic materials with modifiable nanometer-sized pores via a Pictet–Spengler polymerization reaction. This one-pot, four-step synthesis uses concepts based on covalent organic frameworks (COFs) synthesis to produce crystalline two-dimensional materials that were confirmed by PXRD, TEM measurements, and DFT studies. These new materials are structurally analogous to doped graphene and graphene oxide (GO) but, unlike GO, maintain their semiconductive properties when fully functionalized.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structural coherence model for predicting molten salt thermal conductivity informed by the pair distribution function

To enable thermal behavior prediction and design optimization of molten salt reactors, thermal conductivity of molten salts must be characterized in terms of salt composition and temperature. Current theoretical models fail to provide consistent approximations for all halide mixtures, particularly actinide-bearing melts. This study aims to link the short-range order structure of molten salts to the mean free path of energy carriers through a simple structural coherence model informed by the partial pair distribution function. The proposed method is used to predict the thermal conductivity of 33 alkali and alkaline earth halide salts. Predictions approximate experimental measurements with a mean absolute error of 15.7% for dissociating, complexing, and actinide salts, including unary LiCl, NaCl, and MgCl 2 as well as mixtures LiF–NaF–KF (FLiNaK), LiF–BeF 2 (FLiBe), and NaCl–UCl 3 . The work provides evidence for the validity of energy carrier descriptions of molecular-level heat transfer in molten salts, with implications for improved theories of liquid energy transport in general.

Actinide mixtures↗

Adapting a Robot Hand to Specialized Functions

Adaptor enables mechanical and electrical connections made easily between special-purpose end effector and arm of robot or remote mainpulator. Use in prosthetic devices also contemplatd. With adaptor, hand changed quickly from device designed to grasp objects of various sizes and shapes to device intended to do specific task efficiently.

Clark, Keith H.↗

Single-Molecule Electron Transport in Peptoids

Peptoids are structural analogs of peptides in which side chains are appended to the backbone nitrogen rather than the α-carbon. The sequence-defined modularity of peptoids enables precise control over structure−function relationships, enabling applications in energy storage and biomedical materials. Despite recent progress, the role of sequence and conformation on electron transport in peptoid molecules is not fully understood. Here, we synthesize a library of peptoid oligomers and characterize their molecular electronic properties using the scanning tunneling microscope-break junction (STM-BJ) technique. Our results show well-defined electron transport behavior for peptoid sequences containing aromatic side groups lacking hydrogen bonds (H-bonds) and without chemical substitutions at the N−C α position. This behavior fundamentally differs from electron transport in peptides, where H-bond interactions give rise to higher conductance states. All-atom molecular dynamics (MD) simulations are used to understand the conformational heterogeneity of peptoids, and molecular conformations obtained from MD simulations are used in quantum mechanical calculations based on the nonequilibrium Green’s function−density functional theory (NEGF-DFT) formalism. In all cases, computational results are in reasonable qualitative agreement with experiments. Our work demonstrates that the conductance behavior of peptoids depends on monomer identity, including side-chain aromaticity and substitution at the N−C α position. Overall, this work provides new insights into the structure−function relationships governing electron transport in peptoid-based materials and establishes design rules for peptoid-based molecular junctions.

Charge transport↗

Multiparameter optical fiber sensing for energy infrastructure through nanoscale light–matter interactions: From hardware to software, science to commercial opportunities

Monitoring of energy infrastructure through robust yet economical sensing platforms is becoming an area of increased importance, with ubiquitous applications including the electrical grid, natural gas and oil transportation pipelines, H2 infrastructure (storage and transportation), carbon storage, power generation, and subsurface environments. Plasmonic and functional nanomaterial enabled fiber optic sensors show excellent promise for a wide range of sensing applications due to their versatility to be engineered for specific analytes of interest while retaining inherent advantages of the optical fiber sensor platform. Through the design of novel sensing layers, the optical transduction mechanism and wavelength dependence can also be tailored for ease of integration with low-cost interrogation systems enabling an inexpensive yet highly functional optical fiber sensing platform. In addition, recent advances in artificial intelligence and machine learning theoretical methods have been leveraged to simultaneously extract multiple parameters through multi-wavelength interrogation such that unique wavelengths can also serve as unique sensing elements, analogous to electronic nose sensor technologies. The concept of an optical fiber based “photonic nose” via multiple interrogation wavelengths and/or sensor nodes offers a compelling platform technology to realize multiparameter speciation of chemical analytes within complex gas mixtures. In this Perspective, we further generalize the notion of multiparameter sensing through the novel “photonic nervous system” concept based upon low-cost, functionalized optical fiber sensor probes monitoring a variety of distinct analyte classes (physical, chemical, electromagnetic, etc.) simultaneously to provide broad situational awareness via integrated sensors.

Su, Yang-Duan (ORCID:0000000214820902)↗

Benchmarking density functional perturbation theory to enable high-throughput screening of materials for dielectric constant and refractive index

We demonstrate a high-throughput density functional perturbation theory (DFPT) methodology capable of screening compounds for their dielectric properties. The electronic and ionic dielectric tensors are calculated for 88 compounds, where the eigenvalues of the total dielectric tensors are compared with single crystal and polycrystalline experimental values reported in the literature. We find that GGA/PBE has a smaller mean average deviation from experiments (MARD=16.2%) when compared to LDA. The prediction accuracy of DFPT is lowest for compounds that exhibit complex structural relaxation effects (e.g., octahedra rotation in perovskites) and/or strong anharmonicity. Despite some discrepancies between DFPT results and reported experimental values, the high-throughput methodology is found to be useful in identifying interesting compounds by ranking. This is demonstrated by the high Spearman correlation factor (ρ=0.92). Finally, we demonstrate that DFPT provides a good estimate for the refractive index of a compound without calculating the frequency dependence of the dielectric matrix (MARD=5.7%).

36 MATERIALS SCIENCE↗

Functional Performance of an Enabling Atmosphere Revitalization Subsystem Architecture for Deep Space Exploration Missions

A subsystem architecture derived from the International Space Station's (ISS) Atmosphere Revitalization Subsystem (ARS) has been functionally demonstrated. This ISS-derived architecture features re-arranged unit operations for trace contaminant control and carbon dioxide removal functions, a methane purification component as a precursor to enhance resource recovery over ISS capability, operational modifications to a water electrolysis-based oxygen generation assembly, and an alternative major atmospheric constituent monitoring concept. Results from this functional demonstration are summarized and compared to the performance observed during ground-based testing conducted on an ISS-like subsystem architecture. Considerations for further subsystem architecture and process technology development are discussed.

Perry, Jay L.↗