Secondary batteries based on earth-abundant sodium metal anodes are desirable for both stationary and portable electrical energy storage. Room-temperature sodium metal batteries are impractical today because morphological instability during recharge drives rough, dendritic electrodeposition. Chemical instability of liquid electrolytes also leads to premature cell failure as a result of parasitic reactions with the anode. Here we use joint density-functional theoretical analysis to show that the surface diffusion barrier for sodium ion transport is a sensitive function of the chemistry of solid–electrolyte interphase. In particular, we find that a sodium bromide interphase presents an exceptionally low energy barrier to ion transport, comparable to that of metallic magnesium. We evaluate this prediction by means of electrochemical measurements and direct visualization studies. These experiments reveal an approximately three-fold reduction in activation energy for ion transport at a sodium bromide interphase. Direct visualization of sodium electrodeposition confirms large improvements in stability of sodium deposition at sodium bromide-rich interphases.
The structure and function of spines and excitatory synapses are under the dynamic control of multiple signalling networks. Although tyrosine phosphorylation is involved, its regulation and importance are not well understood. Here we study the role of Pyk2, a non-receptor calcium-dependent protein-tyrosine kinase highly expressed in the hippocampus. Hippocampal-related learning and CA1 long-term potentiation are severely impaired in Pyk2-deficient mice and are associated with alterations in NMDA receptors, PSD-95 and dendritic spines. In cultured hippocampal neurons, Pyk2 has autophosphorylation-dependent and -independent roles in determining PSD-95 enrichment and spines density. Pyk2 levels are decreased in the hippocampus of individuals with Huntington and in the R6/1 mouse model of the disease. Normalizing Pyk2 levels in the hippocampus of R6/1 mice rescues memory deficits, spines pathology and PSD-95 localization. Our results reveal a role for Pyk2 in spine structure and synaptic function, and suggest that its deficit contributes to Huntington’s disease cognitive impairments.
Smartphone fluorescence microscopy has various applications in point-of-care (POC) testing and diagnostics, ranging from e.g., quantification of immunoassays, detection of microorganisms, to sensing of viruses. An important need in smartphone-based microscopy and sensing techniques is to improve the detection sensitivity to enable quantification of extremely low concentrations of target molecules. Here, we demonstrate a general strategy to enhance the detection sensitivity of a smartphone-based fluorescence microscope by using surface-enhanced fluorescence (SEF) created by a thin metal-film. In this plasmonic design, the samples are placed on a silver-coated glass slide with a thin spacer, and excited by a laser-diode from the backside through a glass hemisphere, generating surface plasmon polaritons. We optimized this mobile SEF system by tuning the metal-film thickness, spacer distance, excitation angle and polarization, and achieved ~10-fold enhancement in fluorescence intensity compared to a bare glass substrate, which enabled us to image single fluorescent particles as small as 50 nm in diameter and single quantum-dots. Furthermore, we quantified the detection limit of this platform by using DNA origami-based brightness standards, demonstrating that ~80 fluorophores per diffraction-limited spot can be readily detected by our mobile microscope, which opens up new opportunities for POC diagnostics and sensing applications in resource-limited-settings.
The ability to simultaneously image multiple biomolecules in biologically relevant three-dimensional (3D) cell culture environments would contribute greatly to the understanding of complex cellular mechanisms and cell–material interactions. Here, we present a computational framework for label-free quantitative volumetric Raman imaging (qVRI). We apply qVRI to a selection of biological systems: human pluripotent stem cells with their cardiac derivatives, monocytes and monocyte-derived macrophages in conventional cell culture systems and mesenchymal stem cells inside biomimetic hydrogels that supplied a 3D cell culture environment. We demonstrate visualization and quantification of fine details in cell shape, cytoplasm, nucleus, lipid bodies and cytoskeletal structures in 3D with unprecedented biomolecular specificity for vibrational microspectroscopy.
Mughal, Asad J.; Carberry, Benjamin; Speck, James S.; Nakamura, Shuji; DenBaars, Steven P.(Journal of Electronic Materials, Springer Nature, 2017-01-11)[Article]
In this work, we employ a simple two-step growth technique to deposit impurity doped heteroepitaxial thin films of (0001) ZnO onto (111) MgAl2O4 spinel substrates through a combination of atomic layer deposition (ALD) and hydrothermal growth. The hydrothermal layer is doped with Al, Ga, and In through the addition of their respective nitrate salts. We evaluated the effect that varying the concentrations of these dopants has on both the structural and optical properties of these films. It was found that the epitaxial ALD layer created a ⟨111⟩MgAl2O4∥⟨0001⟩ZnO out-of-plane orientation and a ⟨1¯1¯2⟩MgAl2O4∥∥⟨011¯0⟩ZnO in-plane orientation between the film and substrate. The rocking curve line widths ranged between 0.75° and 1.80° depending on dopant concentration. The optical bandgap determined through the Tauc method was between 3.28 eV and 3.39 eV and showed a Burstein-Moss shift with increasing dopant concentration.
Pramana, Stevin S.; Cavallaro, Andrea; Qi, Jiahui; Nicklin, Chris L.; Ryan, Mary P.; Skinner, Stephen J.(Scientific Reports, Springer Nature, 2017-03-02)[Article]
The surface crystallography and chemistry of a LaAlO3 single crystal, a material mainly used as a substrate to deposit technologically important thin films (e.g. for superconducting and magnetic devices), was analysed using surface X-ray diffraction and low energy ion scattering spectroscopy. The surface was determined to be terminated by Al-O species, and was significantly different from the idealised bulk structure. Termination reversal was not observed at higher temperature (600 °C) and chamber pressure of 10−10 Torr, but rather an increased Al-O occupancy occurred, which was accompanied by a larger outwards relaxation of Al from the bulk positions. Changing the oxygen pressure to 10−6 Torr enriched the Al site occupancy fraction at the outermost surface from 0.245(10) to 0.325(9). In contrast the LaO, which is located at the next sub-surface atomic layer, showed no chemical enrichment and the structural relaxation was lower than for the top AlO2 layer. Knowledge of the surface structure will aid the understanding of how and which type of interface will be formed when LaAlO3 is used as a substrate as a function of temperature and pressure, and so lead to improved design of device structures.
Burrell, Thomas; Fozard, Susan; Holroyd, Geoff H.; French, Andrew P.; Pound, Michael P.; Bigley, Christopher J.; James Taylor, C.; Forde, Brian G.(Plant Methods, Springer Nature, 2017-03-01)[Article]
Chemical genetics provides a powerful alternative to conventional genetics for understanding gene function. However, its application to plants has been limited by the lack of a technology that allows detailed phenotyping of whole-seedling development in the context of a high-throughput chemical screen. We have therefore sought to develop an automated micro-phenotyping platform that would allow both root and shoot development to be monitored under conditions where the phenotypic effects of large numbers of small molecules can be assessed.
The ‘Microphenotron’ platform uses 96-well microtitre plates to deliver chemical treatments to seedlings of Arabidopsis thaliana L. and is based around four components: (a) the ‘Phytostrip’, a novel seedling growth device that enables chemical treatments to be combined with the automated capture of images of developing roots and shoots; (b) an illuminated robotic platform that uses a commercially available robotic manipulator to capture images of developing shoots and roots; (c) software to control the sequence of robotic movements and integrate these with the image capture process; (d) purpose-made image analysis software for automated extraction of quantitative phenotypic data. Imaging of each plate (representing 80 separate assays) takes 4 min and can easily be performed daily for time-course studies. As currently configured, the Microphenotron has a capacity of 54 microtitre plates in a growth room footprint of 2.1 m2, giving a potential throughput of up to 4320 chemical treatments in a typical 10 days experiment. The Microphenotron has been validated by using it to screen a collection of 800 natural compounds for qualitative effects on root development and to perform a quantitative analysis of the effects of a range of concentrations of nitrate and ammonium on seedling development.
The Microphenotron is an automated screening platform that for the first time is able to combine large numbers of individual chemical treatments with a detailed analysis of whole-seedling development, and particularly root system development. The Microphenotron should provide a powerful new tool for chemical genetics and for wider chemical biology applications, including the development of natural and synthetic chemical products for improved agricultural sustainability.
We present a visualization pipeline capable of accurate rendering of highly scattering fluorescent neocortical neuronal models. The pipeline is mainly developed to serve the computational neurobiology community. It allows the scientists to visualize the results of their virtual experiments that are performed in computer simulations, or in silico. The impact of the presented pipeline opens novel avenues for assisting the neuroscientists to build biologically accurate models of the brain. These models result from computer simulations of physical experiments that use fluorescence imaging to understand the structural and functional aspects of the brain. Due to the limited capabilities of the current visualization workflows to handle fluorescent volumetric datasets, we propose a physically-based optical model that can accurately simulate light interaction with fluorescent-tagged scattering media based on the basic principles of geometric optics and Monte Carlo path tracing. We also develop an automated and efficient framework for generating dense fluorescent tissue blocks from a neocortical column model that is composed of approximately 31000 neurons.
Our pipeline is used to visualize a virtual fluorescent tissue block of 50 μm3 that is reconstructed from the somatosensory cortex of juvenile rat. The fluorescence optical model is qualitatively analyzed and validated against experimental emission spectra of different fluorescent dyes from the Alexa Fluor family.
We discussed a scientific visualization pipeline for creating images of synthetic neocortical neuronal models that are tagged virtually with fluorescent labels on a physically-plausible basis. The pipeline is applied to analyze and validate simulation data generated from neuroscientific in silico experiments.
Hahn, Aria S.; Altman, Tomer; Konwar, Kishori M.; Hanson, Niels W.; Kim, Dongjae; Relman, David A.; Dill, David L.; Hallam, Steven J.(Scientific Data, Springer Nature, 2017-04-11)[Article]
Advances in high-throughput sequencing are reshaping how we perceive microbial communities inhabiting the human body, with implications for therapeutic interventions. Several large-scale datasets derived from hundreds of human microbiome samples sourced from multiple studies are now publicly available. However, idiosyncratic data processing methods between studies introduce systematic differences that confound comparative analyses. To overcome these challenges, we developed GutCyc, a compendium of environmental pathway genome databases (ePGDBs) constructed from 418 assembled human microbiome datasets using MetaPathways, enabling reproducible functional metagenomic annotation. We also generated metabolic network reconstructions for each metagenome using the Pathway Tools software, empowering researchers and clinicians interested in visualizing and interpreting metabolic pathways encoded by the human gut microbiome. For the first time, GutCyc provides consistent annotations and metabolic pathway predictions, making possible comparative community analyses between health and disease states in inflammatory bowel disease, Crohn’s disease, and type 2 diabetes. GutCyc data products are searchable online, or may be downloaded and explored locally using MetaPathways and Pathway Tools.
Optimal management of subsurface processes requires the characterization of the uncertainty in reservoir description and reservoir performance prediction. For fractured reservoirs, the location and orientation of fractures are crucial for predicting production characteristics. With the help of accurate and comprehensive knowledge of fracture distributions, early water/CO 2 breakthrough can be prevented and sweep efficiency can be improved. However, since the rock property fields are highly non-Gaussian in this case, it is a challenge to estimate fracture distributions by conventional history matching approaches. In this work, a method that combines vector-based level-set parameterization technique and ensemble Kalman filter (EnKF) for estimating fracture distributions is presented. Performing the necessary forward modeling is particularly challenging. In addition to the large number of forward models needed, each model is used for sampling of randomly located fractures. Conventional mesh generation for such systems would be time consuming if possible at all. For these reasons, we rely on a novel polyhedral mesh method using the mimetic finite difference (MFD) method. A discrete fracture model is adopted that maintains the full geometry of the fracture network. By using a cut-cell paradigm, a computational mesh for the matrix can be generated quickly and reliably. In this research, we apply this workflow on 2D two-phase fractured reservoirs. The combination of MFD approach, level-set parameterization, and EnKF provides an effective solution to address the challenges in the history matching problem of highly non-Gaussian fractured reservoirs.
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