Karl A. Hujsak

Flexible ferroelectric organic crystals.

Flexible organic materials possessing useful electrical properties, such as ferroelectricity, are of crucial importance in the engineering of electronic devices. Up until now, however, only ferroelectric polymers have intrinsically met this flexibility requirement, leaving small-molecule organic ferroelectrics with room for improvement. Since both flexibility and ferroelectricity are rare properties on their own, combining them in one crystalline organic material is challenging. Herein, we report that trisubstituted haloimidazoles not only display ferroelectricity and piezoelectricity—the properties that originate from their non-centrosymmetric crystal lattice—but also lend their crystalline mechanical properties to fine-tuning in a controllable manner by disrupting the weak halogen bonds between the molecules. This element of control makes it possible to deliver another unique and highly desirable property, namely crystal flexibility. Moreover, the electrical properties are maintained in the flexible crystals.

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.

Mesophase in a Thiolate-Containing Diacyl Phospholipid Self-Assembled Monolayer

Maintaining the intrinsic features of mesophases is critically important when employing phospholipid self-assemblies to mimic biomembranes. Inorganic solid surfaces provide platforms to support, guide, and analyze organic self-assemblies but impose upon them a tendency to form well-ordered phases not often found in biomembranes. To address this, we measured mesophase formation in a thiolate self-assembled monolayer (SAM) of diacyl phospholipid, 1,2-dipalmitoyl-sn-glycero-3-phosphothioethanol (DPPTE) on Au(111), and provide thermodynamic analysis on the mixing behavior of inequivalent DPPTE acyl chains. Our work has uncovered three fundamental issues that enable mesophase formation: (1) Elimination of templating effects of the solid surface, (2) Weakening intermolecular and molecule-substrate interactions in adsorbates, and (3) Equilibrium through entropy-driven self-assembly. Thus, our work provides a more holistic understanding of phase behavior, from liquid phases to mesophases to highly crystalline phases, in organic self-assemblies on solid surfaces, which may extend their applications in nanodevices and to the wider fields of biology and medicine.

The effects of chemical fixation on the cellular nanostructure

ABSTRACT Chemical fixation is nearly indispensable in the biological sciences, especially in circumstances where cryo‐fixation is not applicable. While universally employed for the preservation of cell organization, chemical fixatives often introduce artifacts that can confound identification of true structures. Since biological research is increasingly probing ever‐finer details of the cellular architecture, it is critical to understand the nanoscale transformation of the cellular organization due to fixation both systematically and quantitatively. In this work, we employed Partial Wave Spectroscopic (PWS) Microscopy, a nanoscale sensitive and label‐free live cell spectroscopic‐imaging technique, to analyze the effects of the fixation process through three commonly used fixation protocols for cells in vitro. In each method investigated, we detected dramatic difference in both nuclear and cytoplasmic nanoarchitecture between live and fixed states. But significantly, despite the alterations in cellular nanoscale organizations after chemical fixation, the population differences in chromatin structure (e.g. induced by a specific chemotherapeutic agent) remains. In conclusion, we demonstrated that the nanoscale cellular arrangement observed in fixed cells was fundamentally divorced from that in live cells, thus the quantitative analysis is only meaningful on the population level. This finding highlights the importance of live cell imaging techniques with nanoscale sensitivity or cryo‐fixation in the interrogation of cellular structure, to complement more traditional chemical fixation methods. HIGHLIGHTSPWS was employed to monitor fixation process for the same cells in vitro.Dramatic changes in cellular nanostructure were observed after fixation.However, the population difference of chromatin structure remains after fixation.

Suppressing Electron Exposure Artifacts: An Electron Scanning Paradigm with Bayesian Machine Learning.

Electron microscopy of biological, polymeric, and other beam-sensitive structures is often hampered by deleterious electron beam interactions. In fact, imaging of such beam-sensitive materials is limited by the allowable radiation dosage rather that capabilities of the microscope itself, which has been compounded by the availability of high brightness electron sources. Reducing dwell times to overcome dose-related artifacts, such as radiolysis and electrostatic charging, is challenging due to the inherently low contrast in imaging of many such materials. These challenges are particularly exacerbated during dynamic time-resolved, fluidic cell imaging, or three-dimensional tomographic reconstruction-all of which undergo additional dosage. Thus, there is a pressing need for the development of techniques to produce high-quality images at ever lower electron doses. In this contribution, we demonstrate direct dose reduction and suppression of beam-induced artifacts through under-sampling pixels, by as much as 80% reduction in dosage, using a commercial scanning electron microscope with an electrostatic beam blanker and a dictionary learning in-painting algorithm. This allows for multiple sparse recoverable images to be acquired at the cost of one fully sampled image. We believe this approach may open new ways to conduct imaging, which otherwise require compromising beam current and/or exposure conditions.

High speed/low dose analytical electron microscopy with dynamic sampling

Technological advances in electron microscopy, particularly improved detectors and aberration correctors, have led to higher throughput and less invasive imaging of materials and biological structures by enhancing signal-to-noise ratios at lower electron exposures. Analytical methods, such as electron energy loss spectroscopy (EELS) and energy dispersive x-ray spectrometry (EDS), have also benefitted and offer a rich set of local elemental and bonding information with nano-or atomic resolution. However, spatially resolved spectrum imaging with EELS and EDS continue to be difficult to scale due to limited detector collection angles or high signal background, requiring hours or even days for full maps. We present the principle and application of a Multi-Objective Autonomous Dynamic Sampling (MOADS) method which can accelerate spectrum mapping in EELS or EDS by over an order of magnitude. Initial guesses about the true spectrum images are constructed as measurements are collected, which allows the prediction of points which contribute information/contrast. In this fashion, an intelligently selected and reduced set of points which best approximate the true spectrum image are autonomously collected on-the-fly to save considerable time and/or radiative area dose. We implemented MOADS as a software add-on to arbitrary commercial Scanning Transmission Electron Microscopes (STEMs) equipped with a Gatan Digital Micrograph (DM, Gatan ©) interface. We demonstrate the efficacy of our proposed method on several prototypical analytical specimens, as well as dose sensitive materials. It is expected that MOADS and similar supervised dynamic sampling approaches may open the exploration of large area analytical maps or the imaging of beam reactive materials not previously thought feasible.

Stage-Rocked Electron Channeling for Crystal Orientation Mapping

Microstructural analysis by crystal orientation mapping of bulk functional materials is an essential and routine operation in the engineering of material properties. Far and away the most successfully employed technique, Electron Backscattered Diffraction (EBSD), provides high spatial resolution information at the cost of limited angular resolution and a distorted imaging condition. In this work, we demonstrate a stage-rocked electron channeling approach as a low-cost orientation mapping alternative to EBSD. This is accomplished by automated electron channeling contrast imaging (ECCI) as the microscope stage physically tilts/rotates a sample through a reduced hemisphere of orientations followed by computational reconstruction of electron channeling patterns (ECP). Referred to as Orientation Mapping by Electron Channeling (OMEC), our method offers advantages in terms of local defect analysis, as it combines the advantages of selected area ECP (SACP) and ECCI. We also illustrate dynamic or “adaptive” sampling schemes to increase the throughput of the technique. Finally, we discuss the implications for sample analysis in which large 3D maps of ECCI images can be routinely constructed of challenging crystalline samples. As an electron channeling-based approach to orientation mapping, OMEC may open new routes to characterize crystalline materials with high angular and spatial resolution.

Increasing the Speed of EELS/EDS Mapping Through Dynamic/Adaptive Sampling Methodologies

1. Department of Materials Science & Engineering, Northwestern University, Evanston, IL. 2. OptimalSensing, Southlake, TX. 3. Department of Electrical and Computer Engineering, Duke University, Durham, NC. 4. Pacific Northwest National Laboratory, Richland, WA. 5. Department of Materials Engineering, University of Liverpool, Liverpool, United Kingdom 6. Electron Probe Instrumentation Center (EPIC) Facility, NUANCE Center, Northwestern University, Evanston, IL.

Micromachined Chip Scale Thermal Sensor for Thermal Imaging

The lateral resolution of scanning thermal microscopy (SThM) has hitherto never approached that of mainstream atomic force microscopy, mainly due to poor performance of the thermal sensor. Herein, we report a nanomechanical system-based thermal sensor (thermocouple) that enables high lateral resolution that is often required in nanoscale thermal characterization in a wide range of applications. This thermocouple-based probe technology delivers excellent lateral resolution (∼20 nm), extended high-temperature measurements >700 °C without cantilever bending, and thermal sensitivity (∼0.04 °C). The origin of significantly improved figures-of-merit lies in the probe design that consists of a hollow silicon tip integrated with a vertically oriented thermocouple sensor at the apex (low thermal mass) which interacts with the sample through a metallic nanowire (50 nm diameter), thereby achieving high lateral resolution. The efficacy of this approach to SThM is demonstrated by imaging embedded metallic nanostructures in silica core-shell, metal nanostructures coated with polymer films, and metal-polymer interconnect structures. The nanoscale pitch and extremely small thermal mass of the probe promise significant improvements over existing methods and wide range of applications in several fields including semiconductor industry, biomedical imaging, and data storage.

Measuring the Autocorrelation Function of Nanoscale Three-Dimensional Density Distribution in Individual Cells Using Scanning Transmission Electron Microscopy, Atomic Force Microscopy, and a New Deconvolution Algorithm

Essentially all biological processes are highly dependent on the nanoscale architecture of the cellular components where these processes take place. Statistical measures, such as the autocorrelation function (ACF) of the three-dimensional (3D) mass-density distribution, are widely used to characterize cellular nanostructure. However, conventional methods of reconstruction of the deterministic 3D mass-density distribution, from which these statistical measures can be calculated, have been inadequate for thick biological structures, such as whole cells, due to the conflict between the need for nanoscale resolution and its inverse relationship with thickness after conventional tomographic reconstruction. To tackle the problem, we have developed a robust method to calculate the ACF of the 3D mass-density distribution without tomography. Assuming the biological mass distribution is isotropic, our method allows for accurate statistical characterization of the 3D mass-density distribution by ACF with two data sets: a single projection image by scanning transmission electron microscopy and a thickness map by atomic force microscopy. Here we present validation of the ACF reconstruction algorithm, as well as its application to calculate the statistics of the 3D distribution of mass-density in a region containing the nucleus of an entire mammalian cell. This method may provide important insights into architectural changes that accompany cellular processes.