Modern nanoelectronics has advanced to a point at which it is impossible to image entire devices and their interconnections non-destructively because of their small feature sizes and the complex three-dimensional structures resulting from their integration on a chip. This metrology gap implies a lack of direct feedback between design and manufacturing processes, and hampers quality control during production, shipment and use. Here we demonstrate that X-ray ptychography-a high-resolution coherent diffractive imaging technique-can create three-dimensional images of integrated circuits of known and unknown designs with a lateral resolution in all directions down to 14.6 nanometres. We obtained detailed device geometries and corresponding elemental maps, and show how the devices are integrated with each other to form the chip. Our experiments represent a major advance in chip inspection and reverse engineering over the traditional destructive electron microscopy and ion milling techniques. Foreseeable developments in X-ray sources, optics and detectors, as well as adoption of an instrument geometry optimized for planar rather than cylindrical samples, could lead to a thousand-fold increase in efficiency, with concomitant reductions in scan times and voxel sizes.

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Ptychographic X-ray computed tomography is a coherent diffractive imaging method that offers nanometer-scale resolution with quantitative contrast. It offers the possibility to study relatively thick samples by using high energy X-ray photons and exploiting the phase contrast. However, the limited depth of field forces a compromise between resolution and sample thickness. Multi-slice techniques have been used to account for propagation effects within the sample, enabling imaging beyond the depth-of-field limit. Here we introduce and experimentally demonstrate our multi-slice algorithms that allow for the reconstruction of multiple object slices and the incident illumination, as well as the retrieval of unknown object thickness. Additionally, through numerical studies, we show that smaller scanning steps surprisingly increase the depth of field, which can be further extended by the use of multi-slice methods under conditions stated by theoretical expressions. The results presented here will be instrumental for the routine implementation of the technique for X-ray nanotomography.

Over the past decade, ptychography has been proven to be a robust tool for non‐destructive high‐resolution quantitative electron, X‐ray and optical microscopy. It allows for quantitative reconstruction of the specimen's transmissivity, as well as recovery of the illuminating wavefront. Additionally, various algorithms have been developed to account for systematic errors and improved convergence. With fast ptychographic microscopes and more advanced algorithms, both the complexity of the reconstruction task and the data volume increase significantly. PtychoShelves is a software package which combines high‐level modularity for easy and fast changes to the data‐processing pipeline, and high‐performance computing on CPUs and GPUs.

High-throughput three-dimensional cryogenic imaging of thick biological specimens is valuable for identifying biologically- or pathologically-relevant features of interest, especially for subsequent correlative studies. Unfortunately, high-resolution imaging techniques at cryogenic conditions often require sample reduction through sequential physical milling or sectioning for sufficient penetration to generate each image of the 3-D stack. This study represents the first demonstration of using ptychographic hard X-ray tomography at cryogenic temperatures for imaging thick biological tissue in a chemically-fixed, frozen-hydrated state without heavy metal staining and organic solvents. Applied to mammalian brain, this label-free cryogenic imaging method allows visualization of myelinated axons and sub-cellular features such as age-related pigmented cellular inclusions at a spatial resolution of ~100 nanometers and thicknesses approaching 100 microns. Because our approach does not require dehydration, staining or reduction of the sample, we introduce the possibility for subsequent analysis of the same tissue using orthogonal approaches that are expected to yield direct complementary insight to the biological features of interest.

The execution and analysis of ever more complex experiments are increasingly challenged by the vast dimensionality of the parameter spaces that underlie investigations in the biological, chemical, physical, and materials sciences. While an increase in data-acquisition rates should allow broader querying of the parameter space, the complexity of experiments and the subtle dependence of the model function on input parameters remains daunting due to the sheer number of variables. To meet these challenges, new strategies for autonomous data acquisition are rapidly coming to fruition, and are being deployed across a spectrum of scientific experiments. One promising direction that is being explored is the use of Gaussian process regression (GPR). GPR is a quick, non-parametric, and robust approximation and uncertainty quantification method that can directly be applied to autonomous data acquisition. In this work, we review and reformulate our most recent contributions to GPR-driven autonomous experimentation in more general terms, and illustrate the functionality of the techniques we present, using new, real-world examples from large experimental facilities in the United States (ALS and NSLS II) and France (ILL). We start by introducing the basics of a GPR-driven autonomous loop with a focus on Gaussian processes. We then shift the focus to the infrastructure that has to be built around GPR to create a closed-loop. Finally, our examples show that Gaussian-process-based autonomous data acquisition is a widely applicable method that can facilitate the optimal utilization of instruments and facilities by enabling the efficient acquisition of high-value datasets.

J. R. (2018). Three dimensional characterization of nickel coarsening in solid oxide cells via ex-situ ptychographic nano-tomography. Journal of Power Sources, 383, 72-79. https://doi. AbstractNickel coarsening is considered a significant cause of solid oxide cell (SOC) performance degradation.Therefore, understanding the morphological changes in the nickel-yttria stabilized zirconia (Ni-YSZ) fuel electrode is crucial for the wide spread usage of SOC technology. This paper reports a study of the initial 3D microstructure evolution of a SOC analyzed in the pristine state and after 3 and 8 hours of annealing at 850 °C, in dry hydrogen. The analysis of the evolution of the same location of the electrode shows a substantial change of the nickel and pore network during the first 3 hours of treatment, while only negligible changes are observed after 8 hours. The nickel coarsening results in loss of connectivity in the nickel network, reduced nickel specific surface area and decreased total triple phase boundary density. For the condition of this experiment, nickel coarsening is shown to be predominantly curvature driven, and changes in the electrode microstructure parameters are discussed in terms of local microstructural evolution.