Branden B. Kappes

Orientation-dependent work function of graphene on Pd(111)

Selected-area diffraction establishes that at least six different in-plane orientations of monolayer graphene on Pd(111) can form during graphene growth. From the intensities of low-energy electron microscopy images as a function of incident electron energy, we find that the work functions of the different rotational domains vary by up to 0.15 eV. Density functional theory calculations show that these significant variations result from orientation-dependent charge transfer from Pd to graphene. These findings suggest that graphene electronics will require precise control over the relative orientation of the graphene and metal contacts.

Moiré superstructures of graphene on faceted nickel islands.

Using scanning tunneling microscopy and spectroscopy, in combination with density functional theory calculations, we investigated the morphology and electronic structure of monolayer graphene grown on the (111) and (110) facets of three-dimensional nickel islands on highly oriented pyrolytic graphite substrate. We observed graphene domains exhibiting hexagonal and striped moiré patterns with periodicities of 22 and 12 Å, respectively, on (111) and (110) facets of the Ni islands. Graphene domains are also observed to grow, as single crystals, across adjacent facets and over facet boundaries. Scanning tunneling spectroscopy data indicate that the graphene layers are metallic on both Ni(111) and Ni(110), in agreement with the calculations. We attribute this behavior to a strong hybridization between the d-bands on Ni and the π-bands of carbon. Our findings point to the possibility of preparing large-area epitaxial graphene layers even on polycrystalline Ni substrates.

Lithiation of silica through partial reduction

We demonstrate the reversible lithiation of SiO2 up to 2/3 Li per Si, and propose a mechanism for it based on molecular dynamics and density functional theory simulations. Our calculations show that neither interstitial Li (no reduction), nor the formation of Li2O clusters and Si–Si bonds (full reduction) are energetically favorable. Rather, two Li effectively break a Si–O bond and become stabilized by oxygen, thus partially reducing the SiO2 anode: this leads to increased anode capacity when the reduction occurs at the Si/SiO2 interface. The resulting LixSiO2 (x<2/3) compounds have band-gaps in the range of 2.0–3.4 eV.

A reactive force field for lithium–aluminum silicates with applications to eucryptite phases

We have parameterized a reactive force field (ReaxFF) for lithium–aluminum silicates using density functional theory (DFT) calculations of structural properties of a number of bulk phase oxides, silicates and aluminates, as well as of several representative clusters. The force field parameters optimized in this study were found to predict lattice parameters and heats of formation of selected condensed phases in excellent agreement with previous DFT calculations and with experiments. We have used the newly developed force field to study the eucryptite phases in terms of their thermodynamic stability and their elastic properties. We have found that (a) these ReaxFF parameters predict the correct order of stability of the three crystalline polymorphs of eucryptite, α, β and γ, and (b) that upon indentation, a new phase appears at applied pressures ≥7 GPa. The high-pressure phase obtained upon indentation is amorphous, as illustrated by the radial distribution functions calculated for different pairs of elements. In terms of elastic properties analysis, we have determined the elements of the stiffness tensor for α- and β-eucryptite at the level of ReaxFF, and discussed the elastic anisotropy of these two polymorphs. Polycrystalline average properties of these eucryptite phases are also reported to serve as ReaxFF predictions of their elastic moduli (in the case of α-eucryptite), or as tests against values known from experiments or DFT calculations (β-eucrypite). The ReaxFF potential reported here can also describe well single-species systems (e.g. Li-metal, Al-metal and condensed phases of silicon), which makes it suitable for investigating structure and properties of suboxides, atomic-scale mechanisms responsible for phase transformations, as well as oxidation–reduction reactions.

Growth structure and work function of bilayer graphene on Pd(111)

Using in situ low-energy electron microscopy and density functional theory, we studied the growth structure and work function of bilayer graphene on Pd(111). Low-energy electron diffraction analysis established that the two graphene layers have multiple rotational orientations relative to each other and the substrate plane. We observedheterogeneous nucleationandsimultaneousgrowthofmultiple,facetedlayerspriortothecompletionof secondlayer.Weproposethatthefacetedshapesareduetothezigzag-terminatededgesboundinggraphenelayers growing under the larger overlying layers. We also found that the work functions of bilayer graphene domains are higher than those of monolayer graphene, and depend sensitively on the orientations of both layers with respect to the substrate. Based on first-principles simulations, we attribute this behavior to oppositely oriented electrostatic dipoles at the graphene/Pd and graphene/graphene interfaces, the strengths of which depend on the orientations of the two graphene layers.

Orientation-dependent binding energy of graphene on palladium

Using density functional theory calculations, we show that the binding strength of a graphene monolayer on Pd(111) can vary between physisorption and chemisorption depending on its orientation. By studying the interfacial charge transfer, we have identified a specific four-atom carbon cluster that is responsible for the local bonding of graphene to Pd(111). The areal density of such clusters varies with the in-plane orientation of graphene, causing the binding energy to change accordingly. Similar investigations can also apply to other metal substrates and suggests that physical, chemical, and mechanical properties of graphene may be controlled by changing its orientation.

Materials Screening Through GPU Accelerated Topological Mapping

Selecting materials with properties tailored to a specific application may be accelerated through materials informatics, but kinetic properties whose calculations are too computationally intensive to be incorporated into materials screening must be replaced with appropriate descriptors. Here we present a highly optimized method for general processing on graphics processing hardware through which we map the interstitial subspace of atomic structures that are used as a qualitative predictor for diffusivity. Additionally, analytical methods that determine the largest channel diameter and identify the optimal path through a material are proposed to characterize this topology. Analysis of the interstitial subspace, along with the theoretical capacities for Li ions, has lead us to select high-capacity lithium ion battery (LIB) materials that display both promising capacities and migration pathways able to support lithium insertion and removal. The result is the identification of Li2MgSi, a LIB anode material with a theoretical capacity of 1023 Ah/kg, from an unfiltered set of 1,754 structures.

Machine Learning to Optimize Additive Manufacturing Parameters for Laser Powder Bed Fusion of Inconel 718

Approximately 3600 samples have been printed to characterize the build parameters for laser powder bed fusion (L-PBF) fabrication of Inconel 718. The tested samples connect pore formation to part orientation, part location and the use of recycled powder. These data serve as the basis for development of a Random Forest Network machine learning (ML) model capable of two-way modeling of process–property and process–structure relationships. These results show how common procedural steps in the setup and execution of L-PBF effect porosity, particularly the formation of keyhole and lack of fusion (LOF) defects, and how data collection, processing, and validation can expose even subtle connections between input features and output parameters using a general ML framework.

Orientation Dependent Binding Energy of Graphene on Pd(111)

Graphene, a two-dimensional crystalline sheet of carbon, has generated considerable attention owing to its ultra-thin geometry, high carrier mobility and tunable band gap, with potential applications in high-performance, low-power electronics and as transparent electrodes. Since graphene–based devices require metal (or metallic) contacts, knowledge of the structural and electronic properties of the metal-graphene interfaces is essential. Previous theoretical studies of graphene-metal contacts indicate that their electronic properties depend on the metal-graphene binding energies. For example, strongly interacting metals can induce a charge transfer from or to graphene, resulting in p- or n-type doping. Here, using Pd(111) as a example substrate, we focus on understanding the influence of the orientation of graphene on its binding to the substrate.Copyright

Interactions of same-row oxygen vacancies on rutile TiO2(110)

Based on a dipolar-elastic model for oxygen vacancies on rutile (110), we evaluated analytically the overall energy of a periodic array of two vacancies and extracted the interaction parameters from total-energy density functional theory (DFT) calculations. Our calculations show that the dipole model holds for next-nearest neighbor vacancies and beyond. The elastic-dipolar interaction vanishes for adjacent vacancies, but they still experience an electrostatic repulsion. The proposed interaction model predicts a vacancy separation distribution that agrees well with that determined in our ultra-high vacuum scanning tunneling microscopy experiments, and provides a perspective for understanding earlier DFT reports.