arXiv subjects

Adam S. Foster

Publications and source records attributed to Adam S. Foster.

26 records · Page 2Linked to original sources

arXiv2020

Electronic and magnetic characterization of epitaxial CrBr$_3$ monolayers

The ability to imprint a given material property to another through proximity effect in layered two-dimensional materials has opened the way to the creation of designer materials. Here, we use molecular-beam epitaxy (MBE) for a direct synthesis of a superconductor-magnet hybrid heterostructure by combining superconducting niobium diselenide (NbSe$_2$) with the monolayer ferromagnetic chromium tribromide (CrBr$_3$). Using different characterization techniques and density-functional theory (DFT) calculations, we have confirmed that the CrBr$_3$ monolayer retains its ferromagnetic ordering with a magnetocrystalline anisotropy favoring an out-of-plane spin orientation. Low-temperature scanning tunneling microscopy (STM) measurements show a slight reduction of the superconducting gap of NbSe$_2$ and the formation of a vortex lattice on the CrBr$_3$ layer in experiments under an external magnetic field. Our results contribute to the broader framework of exploiting proximity effects to realize novel phenomena in 2D heterostructures.

cond-mat.mtrl-sci↗

arXiv2019

Automated Structure Discovery in Atomic Force Microscopy

Atomic force microscopy (AFM) with molecule-functionalized tips has emerged as the primary experimental technique for probing the atomic structure of organic molecules on surfaces. Most experiments have been limited to nearly planar aromatic molecules, due to difficulties with interpretation of highly distorted AFM images originating from non-planar molecules. Here we develop a deep learning infrastructure that matches a set of AFM images with a unique descriptor characterizing the molecular configuration, allowing us to predict the molecular structure directly. We apply this methodology to resolve several distinct adsorption configurations of 1S-camphor on Cu(111) based on low-temperature AFM measurements. This approach will open the door to apply high-resolution AFM to a large variety of systems for which routine atomic and chemical structural resolution on the level of individual objects/molecules would be a major breakthrough.

physics.comp-ph↗

arXiv2019

Data-driven materials science: status, challenges and perspectives

Data-driven science is heralded as a new paradigm in materials science. In this field, data is the new resource, and knowledge is extracted from materials data sets that are too big or complex for traditional human reasoning - typically with the intent to discover new or improved materials or materials phenomena. Multiple factors, including the open science movement, national funding, and progress in information technology, have fueled its development. Such related tools as materials databases, machine learning, and high-throughput methods are now established as parts of the materials research toolset. However, there are a variety of challenges that impede progress in data-driven materials science: data veracity, integration of experimental and computational data, data longevity, standardization, and the gap between industrial interests and academic efforts. In this perspective article, we discuss the historical development and current state of data-driven materials science, building from the early evolution of open science to the rapid expansion of materials data infrastructures. We also review key successes and challenges so far, providing a perspective on the future development of the field.

physics.comp-ph↗

arXiv2019

DScribe: Library of Descriptors for Machine Learning in Materials Science

DScribe is a software package for machine learning that provides popular feature transformations ("descriptors") for atomistic materials simulations. DScribe accelerates the application of machine learning for atomistic property prediction by providing user-friendly, off-the-shelf descriptor implementations. The package currently contains implementations for Coulomb matrix, Ewald sum matrix, sine matrix, Many-body Tensor Representation (MBTR), Atom-centered Symmetry Function (ACSF) and Smooth Overlap of Atomic Positions (SOAP). Usage of the package is illustrated for two different applications: formation energy prediction for solids and ionic charge prediction for atoms in organic molecules. The package is freely available under the open-source Apache License 2.0.

cond-mat.mtrl-sci↗

arXiv2017

Two-dimensional band structure in honeycomb metal-organic frameworks

Metal-organic frameworks (MOFs) are an important class of materials that present intriguing opportunities in the fields of sensing, gas storage, catalysis, and optoelectronics. Very recently, two-dimensional (2D) MOFs have been proposed as a flexible material platform for realizing exotic quantum phases including topological and anomalous quantum Hall insulators. Experimentally, direct synthesis of 2D MOFs has been essentially confined to metal substrates, where the interaction with the substrate masks the intrinsic electronic properties of the MOF. Here, we demonstrate synthesis of 2D honeycomb metal-organic frameworks on a weakly interacting epitaxial graphene substrate. Using low-temperature scanning tunneling microscopy (STM) and atomic force microscopy (AFM) complemented by density-functional theory (DFT) calculations, we show the formation of 2D band structure in the MOF decoupled from the substrate. These results open the experimental path towards MOF-based designer quantum materials with complex, engineered electronic structures.

cond-mat.mtrl-sci↗

arXiv2015

Stick-Slip Control in Nanoscale Boundary Lubrication by Surface Wettability

We study the effect of atomic scale surface-lubricant interactions on nanoscale boundary-lubricated friction, by considering two example surfaces - hydrophilic mica and hydrophobic graphene - confining thin layers of water in molecular dynamics simulations. We observe stick-slip dynamics for thin water films confined by mica sheets, involving periodic breaking-reforming transitions of atomic scale capillary water bridges formed around the potassium ions of mica. However, only smooth sliding without stick-slip events is observed for water confined by graphene, as well as for thicker water layers confined by mica. Thus, our results illustrate how atomic scale details affect the wettability of the confining surfaces, and consequently control the presence or absence of stick-slip dynamics in nanoscale friction.

cond-mat.mtrl-sci↗

arXiv2009

Understanding the atomic-scale contrast in Kelvin Probe Force Microscopy

A numerical analysis of the origin of the atomic-scale contrast in Kelvin probe force microscopy (KPFM) is presented. Atomistic simulations of the tip-sample interaction force field have been combined with a non-contact Atomic Force Microscope/KPFM simulator. The implementation mimics recent experimental results on the (001) surface of a bulk alkali halide crystal for which simultaneous atomic-scale topographical and Contact Potential Difference (CPD) contrasts were reported. The local CPD does reflect the periodicity of the ionic crystal, but not the magnitude of its Madelung surface potential. The imaging mechanism relies on the induced polarization of the ions at the tip-surface interface owing to the modulation of the applied bias voltage. Our findings are in excellent agreement with previous theoretical expectations and experimental observations.

physics.atm-clus↗

arXiv2005

First principles electron transport: finite-element implementation for nanostructures

We have modeled transport properties of nanostructures using the Green's function method within the framework of the density-functional theory. The scheme is computationally demanding so that numerical methods have to be chosen carefully. A typical solution to the numerical burden is to use a special basis-function set, which is tailored to the problem in question, for example, the atomic orbital basis. In this paper we present our solution to the problem. We have used the finite element method (FEM) with a hierarchical high-order polynomial basis, the so-called p-elements. This method allows the discretation error to be controlled in a systematic way. The p-elements work so efficiently that they can be used to solve interesting nanosystems described by non-local pseudopotentials. We demonstrate the potential of the implementation with two different systems. As a test system a simple Na-atom chain between two leads is modeled and the results are compared with several previous calculations. Secondly, we consider a thin hafnium dioxide (HfO2) layer on a silicon surface as a model for a gate structure of the next generation of microelectronics.

physics.comp-ph↗