Elliot Padgett

Atomically engineered ferroic layers yield a room-temperature magnetoelectric multiferroic

Materials that exhibit simultaneous order in their electric and magnetic ground states hold promise for use in next-generation memory devices in which electric fields control magnetism. Such materials are exceedingly rare, however, owing to competing requirements for displacive ferroelectricity and magnetism. Despite the recent identification of several new multiferroic materials and magnetoelectric coupling mechanisms, known single-phase multiferroics remain limited by antiferromagnetic or weak ferromagnetic alignments, by a lack of coupling between the order parameters, or by having properties that emerge only well below room temperature, precluding device applications. Here we present a methodology for constructing single-phase multiferroic materials in which ferroelectricity and strong magnetic ordering are coupled near room temperature. Starting with hexagonal LuFeO3—the geometric ferroelectric with the greatest known planar rumpling—we introduce individual monolayers of FeO during growth to construct formula-unit-thick syntactic layers of ferrimagnetic LuFe2O4 (refs 17, 18) within the LuFeO3 matrix, that is, (LuFeO3)m/(LuFe2O4)1 superlattices. The severe rumpling imposed by the neighbouring LuFeO3 drives the ferrimagnetic LuFe2O4 into a simultaneously ferroelectric state, while also reducing the LuFe2O4 spin frustration. This increases the magnetic transition temperature substantially—from 240 kelvin for LuFe2O4 (ref. 18) to 281 kelvin for (LuFeO3)9/(LuFe2O4)1. Moreover, the ferroelectric order couples to the ferrimagnetism, enabling direct electric-field control of magnetism at 200 kelvin. Our results demonstrate a design methodology for creating higher-temperature magnetoelectric multiferroics by exploiting a combination of geometric frustration, lattice distortions and epitaxial engineering.

Multicomponent Nanomaterials with Complex Networked Architectures from Orthogonal Degradation and Binary Metal Backfilling in ABC Triblock Terpolymers

Selective degradation of block copolymer templates and backfilling the open mesopores is an effective strategy for the synthesis of nanostructured hybrid and inorganic materials. Incorporation of more than one type of inorganic material in orthogonal ways enables the synthesis of multicomponent nanomaterials with complex yet well-controlled architectures; however, developments in this field have been limited by the availability of appropriate orthogonally degradable block copolymers for use as templates. We report the synthesis and self-assembly into cocontinuous network structures of polyisoprene-block-polystyrene-block-poly(propylene carbonate) where the polyisoprene and poly(propylene carbonate) blocks can be orthogonally removed from the polymer film. Through sequential block etching and backfilling the resulting mesopores with different metals, we demonstrate first steps toward the preparation of three-component polymer–inorganic hybrid materials with two distinct metal networks. Multiblock copolymers in which two blocks can be degraded and backfilled independently of each other, without interference from the other, may be used in a wide range of applications requiring periodically ordered complex multicomponent nanoarchitectures.

Tuning the Electrocatalytic Oxygen Reduction Reaction Activity and Stability of Shape-Controlled Pt–Ni Nanoparticles by Thermal Annealing − Elucidating the Surface Atomic Structural and Compositional Changes

Shape-controlled octahedral Pt-Ni alloy nanoparticles exhibit remarkably high activities for the electroreduction of molecular oxygen (oxygen reduction reaction, ORR), which makes them fuel-cell cathode catalysts with exceptional potential. To unfold their full and optimized catalytic activity and stability, however, the nano-octahedra require post-synthesis thermal treatments, which alter the surface atomic structure and composition of the crystal facets. Here, we address and strive to elucidate the underlying surface chemical processes using a combination of ex situ analytical techniques with in situ transmission electron microscopy (TEM), in situ X-ray diffraction (XRD), and in situ electrochemical Fourier transformed infrared (FTIR) experiments. We present a robust fundamental correlation between annealing temperature and catalytic activity, where a ∼25 times higher ORR activity than for commercial Pt/C (2.7 A mgPt-1 at 0.9 VRHE) was reproducibly observed upon annealing at 300 °C. The electrochemical stability, however, peaked out at the most severe heat treatments at 500 °C. Aberration-corrected scanning transmission electron microscopy and energy-dispersive X-ray spectroscopy (EDX) in combination with in situ electrochemical CO stripping/FTIR data revealed subtle, but important, differences in the formation and chemical nature of Pt-rich and Ni-rich surface domains in the octahedral (111) facets. Estimating trends in surface chemisorption energies from in situ electrochemical CO/FTIR investigations suggested that balanced annealing generates an optimal degree of Pt surface enrichment, while the others exhibited mostly Ni-rich facets. The insights from our study are quite generally valid and aid in developing suitable post-synthesis thermal treatments for other alloy nanocatalysts as well.

Nanomaterial datasets to advance tomography in scanning transmission electron microscopy

Electron tomography in materials science has flourished with the demand to characterize nanoscale materials in three dimensions (3D). Access to experimental data is vital for developing and validating reconstruction methods that improve resolution and reduce radiation dose requirements. This work presents five high-quality scanning transmission electron microscope (STEM) tomography datasets in order to address the critical need for open access data in this field. The datasets represent the current limits of experimental technique, are of high quality, and contain materials with structural complexity. Included are tomographic series of a hyperbranched Co2P nanocrystal, platinum nanoparticles on a carbon nanofibre imaged over the complete 180° tilt range, a platinum nanoparticle and a tungsten needle both imaged at atomic resolution by equal slope tomography, and a through-focal tilt series of PtCu nanoparticles. A volumetric reconstruction from every dataset is provided for comparison and development of post-processing and visualization techniques. Researchers interested in creating novel data processing and reconstruction algorithms will now have access to state of the art experimental test data.

Pinning Susceptibility: The effect of dilute, quenched disorder on jamming

We study the effect of dilute pinning on the jamming transition. Pinning reduces the average contact number needed to jam unpinned particles and shifts the jamming threshold to lower densities, leading to a pinning susceptibility, χ_{p}. Our main results are that this susceptibility obeys scaling form and diverges in the thermodynamic limit as χ_{p}∝|ϕ-ϕ_{c}^{∞}|^{-γ_{p}} where ϕ_{c}^{∞} is the jamming threshold in the absence of pins. Finite-size scaling arguments yield these values with associated statistical (systematic) errors γ_{p}=1.018±0.026(0.291) in d=2 and γ_{p}=1.534±0.120(0.822) in d=3. Logarithmic corrections raise the exponent in d=2 to close to the d=3 value, although the systematic errors are very large.

Pt-Richcore/Sn-Richsubsurface/Ptskin Nanocubes As Highly Active and Stable Electrocatalysts for the Ethanol Oxidation Reaction

Direct ethanol fuel cells are one of the most promising electrochemical energy conversion devices for portable, mobile and stationary power applications. However, more efficient and stable and less expensive electrocatalysts are still required. Interestingly, the electrochemical performance of the electrocatalysts toward the ethanol oxidation reaction can be remarkably enhanced by exploiting the benefits of structural and compositional sensitivity and control. Here, we describe the synthesis, characterization, and electrochemical behavior of cubic Pt-Sn nanoparticles. The electrochemical activity of the cubic Pt-Sn nanoparticles was found to be about three times higher than that obtained with unshaped Pt-Sn nanoparticles and six times higher than that of Pt nanocubes. In addition, stability tests indicated the electrocatalyst preserves its morphology and remains well-dispersed on the carbon support after 5000 potential cycles, while a cubic (pure) Pt catalyst exhibited severe agglomeration of the nanoparticles after a similar stability testing protocol. A detailed analysis of the elemental distribution in the nanoparticles by STEM-EELS indicated that Sn dissolves from the outer part of the shell after potential cycling, forming a ∼0.5 nm Pt skin. This particular atomic composition profile having a Pt-rich core, a Sn-rich subsurface layer, and a Pt-skin surface structure is responsible for the high activity and stability.

Advanced Platform for 3D Visualization, Reconstruction, and Segmentation with Electron Tomography

Three-dimensional (3D) characterization of materials at the nanoand meso-scale has become possible with electron tomography (ET) [1-2]. The typical workflow consists of raw data collection with a (scanning) transmission electron microscope, tilt series processing/alignment, tomographic reconstruction, post processing, visualization and analysis. Each step often requires distinct software and has a significant impact to final results. This makes the workflow inefficient and impedes sharing of published or working data among researchers. To address this problem, we have developed an open and extendable platform, tomviz (www.tomviz.org), which integrates the entire ET workflow by providing essential tools from basic image filters to 3D animations (Figure 1).

tomviz: Providing Advanced Electron Tomography by Streamlining Alignment, Reconstruction, and 3D Visualization

Yi Jiang, Elliot Padgett, Marcus D. Hanwell, Cory Quammen, Chris Harris, Shawn Waldon, David A. Muller , Robert Hovden 1. Department of Physics, Cornell University, Ithaca, NY, USA 2. School of Applied & Engineering Physics, Cornell University, Ithaca, NY, USA 3. Kitware, Inc., Clifton Park, NY, USA 4. Kavli Institute at Cornell for Nanoscale Science, Ithaca, NY, USA 5. Department of Materials Science and Engineering, University of Michigan, Ann Arbor, MI, USA

An “Extra Dimension” in Electron Tomography: Automatic Parameter Determination for Next-generation Reconstruction Methods

Electron tomography (ET) reconstructs a 3D model of materials using their 2D projections. Recently, there has been growing interest in developing optimization-based reconstruction techniques, often colloquially referred to as “compressed sensing electron tomography” [1], that obtain reconstructions by formulating and solving a specific optimization problem. Compared with traditional back projection, optimization-based methods are more flexible in using additional prior knowledge about the object to improve reconstruction quality with reduced sampling. However, extra parameters introduced in optimization problems often have significant impacts on images, yet are seldom explored in literature. Here, we demonstrate the use of a power spectrum analysis to facilitate robust automatic parameter selection for ET using the popular total variation (TV) minimization method.

Sampling limits for electron tomography with sparsity-exploiting reconstructions

Electron tomography (ET) has become a standard technique for 3D characterization of materials at the nano-scale. Traditional reconstruction algorithms such as weighted back projection suffer from disruptive artifacts with insufficient projections. Popularized by compressed sensing, sparsity-exploiting algorithms have been applied to experimental ET data and show promise for improving reconstruction quality or reducing the total beam dose applied to a specimen. Nevertheless, theoretical bounds for these methods have been less explored in the context of ET applications. Here, we perform numerical simulations to investigate performance of ℓ1-norm and total-variation (TV) minimization under various imaging conditions. From 36,100 different simulated structures, our results show specimens with more complex structures generally require more projections for exact reconstruction. However, once sufficient data is acquired, dividing the beam dose over more projections provides no improvements-analogous to the traditional dose-fraction theorem. Moreover, a limited tilt range of ±75° or less can result in distorting artifacts in sparsity-exploiting reconstructions. The influence of optimization parameters on reconstructions is also discussed.