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Critical Role of Framework Flexibility and Disorder in Driving High Ionic Conductivity in LiNbOCl 4
Understanding Li-ion transport is key for the rational design of superionic solid electrolytes with exceptional ionic conductivities. LiNbOCl 4 is reported to be one of the most highly conducting materials in the recently realized new class of soft oxyhalide solid electrolytes, exhibiting an ionic conductivity of ~11 mS·cm -1 . Here, we apply X-ray/neutron diffraction and pair distribution function analysis - coupled with density functional theory/ab-initio molecular dynamics - to determine a structural model that provides a rationale for the high conductivity that we observe experimentally in this nanocrystalline solid. We show that it arises from unusually high framework flexibility at room temperature. This owes to isolated 1-D [NbOCl 4 ] - anionic chains which exhibit energetically favorable orientational disorder that is - in turn - correlated to multiple, disordered and equi-energetic Li + sites in the lattice. As the Li-ions sample the 3-D energy landscape with a fast predicted diffusion coefficient of 5.1 x 10 -7 cm 2 /s at room temperature (σ i calc = 17.4 mS·cm -1 ), the inorganic polymer chains can reorient or vice versa. The activation energy barrier for Li migration through the frustrated energy landscape is especially reduced by the elastic nature of the NbO 2 Cl 4 octahedra evident from very widely dispersed Cl-Nb-Cl bond angles in AIMD snapshots at 300 K. The phonon spectra are predominantly influenced by Cl vibrations in the low energy range, and there is strong overlap between the framework (Cl, Nb) and Li partial pDOS in the region between 1.2 - 4.0 THz. The framework flexibility is also reflected in a relatively low bulk modulus of 22 GPa. In conclusion, our findings pave the way for investigation of future “flex-ion” inorganic solids and open up a new direction for the design of high conductivity, soft solid electrolytes for all-solid-state batteries.
Wavefunction theory and density functional theory analysis of ground and excited electronic states of TaB and WB
Full potential energy curves, electronic configurations, spectroscopic parameters, dipole moments, and energetics of ground and excited electronic states of TaB and WB were studied using MRCI, MRCI+Q, CCSD(T), and DFT levels of theory.
A Statistical Assessment of Zener Diode Behavior Using Functional Data Analysis.
Abstract not provided.
Recent Advances in Functional Data Analysis for Electronic Device Data
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TH-E-BRF-07: Raman Spectroscopy for Radiation Treatment Response Assessment in a Lung Metastases Mouse Model
Purpose: Raman spectroscopy is an optical spectroscopic method used to probe chemical information about a target tissue. Our goal was to investigate whether Raman spectroscopy is able to distinguish lung tumors from normal lung tissue and whether this technique can identify the molecular changes induced by radiation. Methods: 4T1 mouse breast cancer cells were implanted subcutaneously into the flanks of 6 Balb/C female mice. Four additional mice were used as “normal lung” controls. After 14 days, 3 mice bearing tumors received 6Gy to the left lung with 6MV photons and the other three were treated as “unirradiated tumor” controls. At a 24-hour time point, lungs were excised and the specimens were sectioned using a cryostat; alternating sections were either stained with hematoxylin and eosin (H and E) for evaluation by a pathologist or unstained for Raman measurements. 240 total Raman spectra were collected; 84 from normal lung controls; 63 from unirradiated tumors and 64 from tumors irradiated with 6Gy in a single fraction. Raman spectra were also collected from normal lung tissues of mice with unirradiated tumors. Principal component analysis (PCA) and discriminant function analysis (DFA) were performed to analyze the data. Results: Raman bands assignable to DNA/RNA showed prominent contributions in tumor tissues while Raman bands associated with hemoglobin showed strong contributions in normal lung tissue. PCA/DFA analysis identified normal lung tissue and tumor with 100% and 98.4% accuracy, respectively, relative to pathologic scoring. Additionally, normal lung tissues from unirradiated mice bearing tumors were classified as normal with 100% accuracy. In a model consisting of unirradiated and irradiated tumors identification accuracy was 79.4% and 93.8% respectively, relative to pathologic assessment. Conclusion: Initial results demonstrate the promise for Raman spectroscopy in the diagnosis normal vs. lung metastases as well as the assessment of radiation therapy response. Further investigations are needed to validate these results. This study was supported in part by a research grant from Varian Medical Systems, Palo Alto, CA.
Structural and Mutational Analysis of Functional Differentiation between Synaptotagmins-1 and -7
Synaptotagmins are known to mediate diverse forms of Ca{sup 2+}-triggered exocytosis through their C{sub 2} domains, but the principles underlying functional differentiation among them are unclear. Synaptotagmin-1 functions as a Ca{sup 2+} sensor in neurotransmitter release at central nervous system synapses, but synaptotagmin-7 does not, and yet both isoforms act as Ca{sup 2+} sensors in chromaffin cells. To shed light into this apparent paradox, we have performed rescue experiments in neurons from synaptotagmin-1 knockout mice using a chimera that contains the synaptotagmin-1 sequence with its C{sub 2}B domain replaced by the synaptotagmin-7 C{sub 2}B domain (Syt1/7). Rescue was not achieved either with the WT Syt1/7 chimera or with nine mutants where residues that are distinct in synaptotagmin-7 were restored to those present in synaptotagmin-1. To investigate whether these results arise because of unique conformational features of the synaptotagmin-7 C{sub 2}B domain, we determined its crystal structure at 1.44 {angstrom} resolution. The synaptotagmin-7 C{sub 2}B domain structure is very similar to that of the synaptotagmin-1 C{sub 2}B domain and contains three Ca{sup 2+}-binding sites. Two of the Ca{sup 2+}-binding sites of the synaptotagmin-7 C{sub 2}B domain are also present in the synaptotagmin-1 C{sub 2}B domain and have analogous ligands to those determined for the latter by NMR spectroscopy, suggesting that a discrepancy observed in a crystal structure of the synaptotagmin-1 C{sub 2}B domain arose from crystal contacts. Overall, our results suggest that functional differentiation in synaptotagmins arises in part from subtle sequence changes that yield dramatic functional differences.
Machine learning to predict microbial community functions: An analysis of dissolved organic carbon from litter decomposition
Not Available
Chemical Genetic Analysis and Functional Characterization of Staphylococcal Wall Teichoic Acid 2-Epimerases Reveals Unconventional Antibiotic Drug Targets
Here we describe a chemical biology strategy performed in Staphylococcus aureus and Staphylococcus epidermidis to identify MnaA, a 2-epimerase that we demonstrate interconverts UDP-GlcNAc and UDP-ManNAc to modulate substrate levels of TarO and TarA wall teichoic acid (WTA) biosynthesis enzymes. Genetic inactivation of mnaA results in complete loss of WTA and dramatic in vitro β-lactam hypersensitivity in methicillin-resistant S. aureus (MRSA) and S. epidermidis (MRSE). Likewise, the β-lactam antibiotic imipenem exhibits restored bactericidal activity against mnaA mutants in vitro and concomitant efficacy against 2-epimerase defective strains in a mouse thigh model of MRSA and MRSE infection. Interestingly, whereas MnaA serves as the sole 2-epimerase required for WTA biosynthesis in S. epidermidis, MnaA and Cap5P provide compensatory WTA functional roles in S. aureus. We also demonstrate that MnaA and other enzymes of WTA biosynthesis are required for biofilm formation in MRSA and MRSE. We further determine the 1.9Å crystal structure of S. aureus MnaA and identify critical residues for enzymatic dimerization, stability, and substrate binding. Finally, the natural product antibiotic tunicamycin is shown to physically bind MnaA and Cap5P and inhibit 2-epimerase activity, demonstrating that it inhibits a previously unanticipated step in WTA biosynthesis. In summary, MnaA serves as a new Staphylococcal antibiotic target with cognate inhibitors predicted to possess dual therapeutic benefit: as combination agents to restore β-lactam efficacy against MRSA and MRSE and as non-bioactive prophylactic agents to prevent Staphylococcal biofilm formation.
Generation and Application of NCF Data Network Layers for Risk Analysis via Functional Decomposition .
Abstract not provided.
Improving Density Curve Predictions and Uncertainty Quantification with Functional Data Analysis [Slides]
Los Alamos National Laboratory (LANL) has developed advanced simulation methods for predicting subsurface flow.
A Statistical Assessment of Zener Diode Behavior Using Functional Data Analysis
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Recent Advances in Functional Data Analysis for Electronic Devices
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Density Functional Theory Analysis of Candidate Tritium Permeation Barriers for Vanadium Alloys as a Fusion Structural Material
Vanadium alloys are being considered as a candidate structural material for the breeder blanket component of future fusion reactors due to their good thermal conductivity, low activation, and chemical compatibility with FLiBe. However, vanadium has a high hydrogen solubility, resulting in hydrogen diffusion and trapping in the vanadium structural alloy and lower than expected tritium breeding ratios. To mitigate the permeation of hydrogen into the structural alloy, a tritium permeation barrier will be coated onto the vanadium alloy. Multiple materials have been proposed as candidate tritium permeation barriers, but the extent to which each of these materials impacts hydrogen diffusion and trapping is still unknown. In this project, we perform atomic-scale calculations to narrow down the list of potential tritium permeation barrier candidates and to understand the mechanisms through which hydrogen diffusion is affected in these materials.
Constructing Networks of Organelle Functional Modules in Arabidopsis
With the rapid accumulation of gene expression data, gene functional module identification has become a widely used approach in functional analysis. However, tools to identify organelle functional modules and analyze their relationships are still missing. We present a soft thresholding approach to construct networks of functional modules using gene expression datasets, in which nodes are strongly co-expressed genes that encode proteins residing in the same subcellular localization, and links represent strong inter-module connections. Our algorithm has three steps. First, we identify functional modules by analyzing gene expression data. Next, we use a self-adaptive approach to construct a mixed network of functional modules and genes. Finally, we link functional modules that are tightly connected in the mixed network. Analysis of experimental data from Arabidopsis demonstrates that our approach is effective in improving the interpretability of high-throughput transcriptomic data and inferring function of unknown genes.