Vincent De Andrade

Heterogeneous silicon mesostructures for lipid-supported bioelectric interfaces

Silicon-based materials have widespread application as biophysical tools and biomedical devices. Here we introduce a biocompatible and degradable mesostructured form of silicon with multiscale structural and chemical heterogeneities. The material was synthesized using mesoporous silica as a template through a chemical-vapor-deposition process. It has an amorphous atomic structure, an ordered nanowire-based framework, and random submicrometre voids, and shows an average Young’s modulus that is 2–3 orders of magnitude smaller than that of single crystalline silicon. In addition, we used the heterogeneous silicon mesostructures to design a lipid-bilayer-supported bioelectric interface that is remotely controlled and temporally transient, and that permits non-genetic and subcellular optical modulation of the electrophysiology dynamics in single dorsal root ganglia neurons. Our findings suggest that the biomimetic expansion of silicon into heterogeneous and deformable forms can open up opportunities in extracellular biomaterial or bioelectric systems.

Experimental evidence of reaction‐induced fracturing during olivine carbonation

Author(s): Zhu, W; Fusseis, F; Lisabeth, H; Xing, T; Xiao, X; De Andrade, V; Karato, SI | Abstract: ©2016. American Geophysical Union. All Rights Reserved. Mineral carbonation, a process that binds CO2 in the form of carbonates by silicate weathering, is widespread on the Earths surface. Because of the abundance of silicate rocks and the permanence of the carbonated solids, sequestering CO2 via mineral carbonation has generated lots of interests. However, it is unclear how the fluid-rock reaction proceeds to completion in spite of an increasing solid volume. We conducted a mineral carbonation experiment in which a sintered olivine aggregate reacted with a sodium bicarbonate solution at reservoir conditions. Time-resolved synchrotron X-ray microtomographic images show cracks in polygonal patterns arising in the surface layers and propagating into the interior of the olivine aggregate. The nanotomography data reveal that the incipient cracks intersect at right angles. We infer that stretching due to nonuniform volume expansion generates polygonal cracking of the surfaces. Our data shed new lights on the processes that control hydration and carbonation of peridotite.

Nanoscale 3D imaging at the Advanced Photon Source

Over the past decade, technology breakthroughs in the field of x-ray optics have enabled the development of advanced imaging nanoprobes at third-generation synchrotrons.1–11 X-rays have unique capabilities in terms of resolution, sensitivity, and speed, and by combining these properties with their ability to penetrate matter, these new instruments have played an important role in the recent advent of nano-material-related research.12 The gap— in terms of spatial resolution—between such x-ray instruments and electron microscopes, however, still needs to be reduced. In addition, it remains a challenge to offer in situ measurement capabilities while simultaneously pushing the spatial resolution limits. Conceptually, transmission x-ray microscopes (TXMs) are similar to optical visible light microscopes. In these instruments, tunable monochromatic x-rays illuminate the condenser—either an ellipsoidal glass mono-capillary or special type of diffraction grating known as a beam-shaping condenser (BSC)—and a Fresnel zone plate (FZP) is used as the objective lens to magnify the images or radiographs (see Figure 1). TXMs are also full-field imaging instruments, meaning that the snapshot images of absorption contrasts inside samples are acquired with 2D detectors (commonly four megapixel sensors). It is this type of full-field imaging—much faster than raster scan modes of pencil beam nanoprobes—which makes dynamic studies possible. To take on the challenge of nano-materials science in the fields of energy storage, microelectronics, nano-porous material functions, as well as life, Earth, and environmental sciences, we have developed a new in-house TXM at the Advanced Photon Source (sector 32-ID) of the Argonne National Laboratory. This instrument has replaced an older, first-generation commercial system,13 by providing a superior analytical imaging performance and in situ capabilities. In addition, our TXM supports a Figure 1. (a) Schematic representation of a transmission x-ray microscope (TXM) used for nano-tomography studies. (b) Photograph of the TXM that has been developed at sector 32-ID of the Argonne National Laboratory’s Advanced Photon Source. -CT: Micro-computed tomography.

Deciphering temperature, pressure and oxygen-activity conditions of chlorite formation

Abstract The advantages and limits of empirical, semi-empirical and thermodynamic methods devoted to the estimation of chlorite-formation temperature are discussed briefly. The results of semi- empirical and thermodynamic approaches with different assumptions regarding the redox state of iron in chlorite are compared for a large set of natural data covering a range of pressure conditions from a few hundred bars to 18 kbar and temperature from 100 to 500°C. The T-XFe3+ evolution estimated using the thermodynamic approach of Vidal et al. (2005) shows a systematic increase in XFe3+ with decreasing temperature, which is compatible with the decrease in a02 buffered by magnetite- or hematite-chlorite equilibrium. This trend as well as the observed increase in vacancies in chlorite with decreasing temperature is interpreted as the incorporation of Fe3+-Sudoite. The standard-state properties of this end- member have been derived to reproduce the observed T-aO2-XFe3+ evolutions. It can be used to estimate T-aO2-XFe3 values with a Chl-Qtz-H2O multi-equilibrium approach. When combining our results with those of other studies published recently, it appears that thermodynamic approaches and mapping techniques developed for metamorphic rocks can be used to discuss the conditions of formation of very low-grade rocks where kinetics is much more sluggish than in metamorphic rocks. This requires use of appropriate analytical tools and techniques with a spatial resolution of a few hundred nanometres.

Statistical petrology reveals a link between supercontinents cycle and mantle global climate

Abstract The breakup of supercontinents is accompanied by the emplacement of continental flood basalts and dike swarms, the origin of which is often attributed to mantle plumes. However, convection modeling has showed that the formation of supercontinents result in the warming of the sub-continental asthenospheric mantle (SCAM), which could also explain syn-breakup volcanism. Temperature variations during the formation then breakup of supercontinents are therefore fundamental to understand volcanism related to supercontinent cycles. Magmatic minerals record the thermal state of their magmatic sources. Here we present a data mining analysis on the first global compilation of chemical information on magmatic rocks and minerals formed over the past 600 million years: a time period spanning the aggregation and breakup of Pangea, the last supercontinent. We show that following a period of increasingly hotter Mgrich magmatism with dominant tholeiitic affinity during the aggregation of Pangea, lower-temperature minerals crystallized within Mg-poorer magma with a dominant calc-alkaline affinity during Pangea disassembly. These trends reflect temporal changes in global mantle climate and global plate tectonics in response to continental masses assembly and dispersal. We also show that the final amalgamation of Pangea at ~300 Myr led to a long period of lithospheric collapse and cooling until the major step of Pangea disassembly started at ~125 Myr. The geological control on the geosphere magma budget has implications on the oxidation state and temperature of the Earth’s outer envelopes in the Phanerozoic and may have exerted indirect influence on the evolution of climate and life on Earth.

Quantifying Mesoscale Neuroanatomy Using X-Ray Microtomography

Visual Abstract Methods for resolving the three-dimensional (3D) microstructure of the brain typically start by thinly slicing and staining the brain, followed by imaging numerous individual sections with visible light photons or electrons. In contrast, X-rays can be used to image thick samples, providing a rapid approach for producing large 3D brain maps without sectioning. Here we demonstrate the use of synchrotron X-ray microtomography (µCT) for producing mesoscale (∼1 µm 3 resolution) brain maps from millimeter-scale volumes of mouse brain. We introduce a pipeline for µCT-based brain mapping that develops and integrates methods for sample preparation, imaging, and automated segmentation of cells, blood vessels, and myelinated axons, in addition to statistical analyses of these brain structures. Our results demonstrate that X-ray tomography achieves rapid quantification of large brain volumes, complementing other brain mapping and connectomics efforts.

Low-dose x-ray tomography through a deep convolutional neural network

Synchrotron-based X-ray tomography offers the potential for rapid large-scale reconstructions of the interiors of materials and biological tissue at fine resolution. However, for radiation sensitive samples, there remain fundamental trade-offs between damaging samples during longer acquisition times and reducing signals with shorter acquisition times. We present a deep convolutional neural network (CNN) method that increases the acquired X-ray tomographic signal by at least a factor of 10 during low-dose fast acquisition by improving the quality of recorded projections. Short-exposure-time projections enhanced with CNNs show signal-to-noise ratios similar to long-exposure-time projections. They also show lower noise and more structural information than low-dose short-exposure acquisitions post-processed by other techniques. We evaluated this approach using simulated samples and further validated it with experimental data from radiation sensitive mouse brains acquired in a tomographic setting with transmission X-ray microscopy. We demonstrate that automated algorithms can reliably trace brain structures in low-dose datasets enhanced with CNN. This method can be applied to other tomographic or scanning based X-ray imaging techniques and has great potential for studying faster dynamics in specimens

Rapid alignment of nanotomography data using joint iterative reconstruction and reprojection

As x-ray and electron tomography is pushed further into the nanoscale, the limitations of rotation stages become more apparent, leading to challenges in the alignment of the acquired projection images. Here we present an approach for rapid post-acquisition alignment of these projections to obtain high quality three-dimensional images. Our approach is based on a joint estimation of alignment errors, and the object, using an iterative refinement procedure. With simulated data where we know the alignment error of each projection image, our approach shows a residual alignment error that is a factor of a thousand smaller, and it reaches the same error level in the reconstructed image in less than half the number of iterations. We then show its application to experimental data in x-ray and electron nanotomography.

3D calcite heterostructures for dynamic and deformable mineralized matrices

Scales are rooted in soft tissues, and are regenerated by specialized cells. The realization of dynamic synthetic analogues with inorganic materials has been a significant challenge, because the abiological regeneration sites that could yield deterministic growth behavior are hard to form. Here we overcome this fundamental hurdle by constructing a mutable and deformable array of three-dimensional calcite heterostructures that are partially locked in silicone. Individual calcite crystals exhibit asymmetrical dumbbell shapes and are prepared by a parallel tectonic approach under ambient conditions. The silicone matrix immobilizes the epitaxial nucleation sites through self-templated cavities, which enables symmetry breaking in reaction dynamics and scalable manipulation of the mineral ensembles. With this platform, we devise several mineral-enabled dynamic surfaces and interfaces. For example, we show that the induced growth of minerals yields localized inorganic adhesion for biological tissue and reversible focal encapsulation for sensitive components in flexible electronics.Minerals are rarely explored as building blocks for dynamic inorganic materials. Here, the authors derive inspiration from fish scales to create mutable surfaces based on arrays of calcite crystals, in which one end of each crystal is immobilized in and regenerated from silicone, and the other functional end is left exposed.

Improved tomographic reconstruction of large-scale real-world data by filter optimization

In advanced tomographic experiments, large detector sizes and large numbers of acquired datasets can make it difficult to process the data in a reasonable time. At the same time, the acquired projections are often limited in some way, for example having a low number of projections or a low signal-to-noise ratio. Direct analytical reconstruction methods are able to produce reconstructions in very little time, even for large-scale data, but the quality of these reconstructions can be insufficient for further analysis in cases with limited data. Iterative reconstruction methods typically produce more accurate reconstructions, but take significantly more time to compute, which limits their usefulness in practice. In this paper, we present the application of the SIRT-FBP method to large-scale real-world tomographic data. The SIRT-FBP method is able to accurately approximate the simultaneous iterative reconstruction technique (SIRT) method by the computationally efficient filtered backprojection (FBP) method, using precomputed experiment-specific filters. We specifically focus on the many implementation details that are important for application on large-scale real-world data, and give solutions to common problems that occur with experimental data. We show that SIRT-FBP filters can be computed in reasonable time, even for large problem sizes, and that precomputed filters can be reused for future experiments. Reconstruction results are given for three different experiments, and are compared with results of popular existing methods. The results show that the SIRT-FBP method is able to accurately approximate iterative reconstructions of experimental data. Furthermore, they show that, in practice, the SIRT-FBP method can produce more accurate reconstructions than standard direct analytical reconstructions with popular filters, without increasing the required computation time.