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Stephen Jesse

Publications and source records attributed to Stephen Jesse.

At least 37 records · Page 2Linked to original sources

Controlling hydrocarbon transport and electron beam induced deposition on single layer graphene: toward atomic scale synthesis in the scanning transmission electron microscope

Focused electron beam induced deposition (FEBID) is a direct write technique for depositing materials on a support substrate akin to 3D printing with an electron beam (e-beam). Opportunities exist for merging this existing technique with aberration-corrected scanning transmission electron microscopy to achieve molecular- or atomic-level spatial precision. Several demonstrations have been performed using graphene as the support substrate. A common challenge that arises during this process is e-beam-induced hydrocarbon deposition, suggesting greater control over the sample environment is needed. Various strategies exist for cleaning graphene in situ. One of the most effective methods is to rapidly heat to high temperatures, e.g., 600 C or higher. While this can produce large areas of what appears to be atomically clean graphene, mobile hydrocarbons can still be present on the surfaces. Here, we show that these hydrocarbons are primarily limited to surface migration and demonstrate an effective method for interrupting the flow using e-beam deposition to form corralled hydrocarbon regions. This strategy is effective for maintaining atomically clean graphene at high temperatures where hydrocarbon mobility can lead to substantial accumulation of unwanted e-beam deposition.

cond-mat.mtrl-sci↗

Doping transition-metal atoms in graphene for atomic-scale tailoring of electronic, magnetic, and quantum topological properties

Atomic-scale fabrication is an outstanding challenge and overarching goal for the nanoscience community. The practical implementation of moving and fixing atoms to a structure is non-trivial considering that one must spatially address the positioning of single atoms, provide a stabilizing scaffold to hold structures in place, and understand the details of their chemical bonding. Free-standing graphene offers a simplified platform for the development of atomic-scale fabrication and the focused electron beam in a scanning transmission electron microscope can be used to locally induce defects and sculpt the graphene. In this scenario, the graphene forms the stabilizing scaffold and the experimental question is whether a range of dopant atoms can be attached and incorporated into the lattice using a single technique and, from a theoretical perspective, we would like to know which dopants will create technologically interesting properties. Here, we demonstrate that the electron beam can be used to selectively and precisely insert a variety of transition metal atoms into graphene with highly localized control over the doping locations. We use first-principles density functional theory calculations with direct observation of the created structures to reveal the energetics of incorporating metal atoms into graphene and their magnetic, electronic, and quantum topological properties.

cond-mat.mtrl-sci↗

The role of temperature on defect diffusion and nanoscale patterning in graphene

Graphene is of great scientific interest due to a variety of unique properties such as ballistic transport, spin selectivity, the quantum hall effect, and other quantum properties. Nanopatterning and atomic scale modifications of graphene are expected to enable further control over its intrinsic properties, providing ways to tune the electronic properties through geometric and strain effects, introduce edge states and other local or extended topological defects, and sculpt circuit paths. The focused beam of a scanning transmission electron microscope (STEM) can be used to remove atoms, enabling milling, doping, and deposition. Utilization of a STEM as an atomic scale fabrication platform is increasing; however, a detailed understanding of beam-induced processes and the subsequent cascade of aftereffects is lacking. Here, we examine the electron beam effects on atomically clean graphene at a variety of temperatures ranging from 400 to 1000 C. We find that temperature plays a significant role in the milling rate and moderates competing processes of carbon adatom coalescence, graphene healing, and the diffusion (and recombination) of defects. The results of this work can be applied to a wider range of 2D materials and introduce better understanding of defect evolution in graphite and other bulk layered materials.

cond-mat.mes-hall↗

Doping of Cr in Graphene Using Electron Beam Manipulation for Functional Defect Engineering

Chromium atoms in graphene have been proposed to exhibit magnetic moments and spin-selective conducting states depending on the local bonding geometry within the graphene structure, which could lead to interesting applications in spintronics. Despite this interest, there are few direct experimental reports of Cr dopants in graphene even though it is theorized to be stable. Here, we demonstrate the introduction of single Cr dopant atoms into the graphene lattice and onto graphene edges through the controlled use of a focused electron beam in a scanning transmission electron microscope. We show local control of doping locations and when coupled with targeted in situ milling during scanning of the e-beam, these strategies demonstrate an important component of the fabrication of tailored nanostructured devices in the electron microscope. The approach is validated with first principles calculations to understand synthesis pathways during fabrication and reveal the energetics and local properties of Cr atoms embedded in graphene; e.g., Cr doping can convert graphene into a magnetic and semiconducting material, which suggests Cr-doped graphene can be used as a building block for potential electronic devices and a means to construct them.

cond-mat.mtrl-sci↗

The Synthescope: A Vision for Combining Synthesis with Atomic Fabrication

The scanning transmission electron microscope, a workhorse instrument in materials characterization, is being transformed into an atomic-scale material manipulation platform. With an eye on the trajectory of recent developments and the obstacles toward progress in this field, we provide a vision for a path toward an expanded set of capabilities and applications. We reconceptualize the microscope as an instrument for fabrication and synthesis with the capability to image and characterize atomic-scale structural formation as it occurs. Further development and refinement of this approach may have substantial impact on research in microelectronics, quantum information science, and catalysis where precise control over atomic scale structure and chemistry of a few "active sites" can have a dramatic impact on larger scale functionality and where developing a better understanding of atomic scale processes can help point the way to larger scale synthesis approaches.

physics.app-ph↗

A dynamic Bayesian optimized active recommender system for curiosity-driven Human-in-the-loop automated experiments

Optimization of experimental materials synthesis and characterization through active learning methods has been growing over the last decade, with examples ranging from measurements of diffraction on combinatorial alloys at synchrotrons, to searches through chemical space with automated synthesis robots for perovskites. In virtually all cases, the target property of interest for optimization is defined apriori with limited human feedback during operation. In contrast, here we present the development of a new type of human in the loop experimental workflow, via a Bayesian optimized active recommender system (BOARS), to shape targets on the fly, employing human feedback. We showcase examples of this framework applied to pre-acquired piezoresponse force spectroscopy of a ferroelectric thin film, and then implement this in real time on an atomic force microscope, where the optimization proceeds to find symmetric piezoresponse amplitude hysteresis loops. It is found that such features appear more affected by subsurface defects than the local domain structure. This work shows the utility of human-augmented machine learning approaches for curiosity-driven exploration of systems across experimental domains. The analysis reported here is summarized in Colab Notebook for the purpose of tutorial and application to other data: https://github.com/arpanbiswas52/varTBO

cs.LG↗

Direct-Writing Atom-by-Atom

Direct-write processes enable the alteration or deposition of materials in a continuous, directable, sequential fashion. In this work we demonstrate an electron beam direct-write process in an aberration-corrected scanning transmission electron microscope. This process has several fundamental differences from conventional electron beam induced deposition techniques, where the electron beam dissociates precursor gases into chemically reactive products that bond to a substrate. Here, we use elemental tin (Sn) as a precursor and employ a different mechanism to facilitate deposition. The atomic-sized electron beam is used to generate chemically reactive point defects at desired locations in a graphene substrate. Temperature control of the sample is used to enable the precursor atoms to migrate across the surface and bond to the defect sites thereby enabling atom-by-atom direct-writing.

cond-mat.mtrl-sci↗

A platform for in situ synthesis in a STEM

The engineering of quantum materials requires the development of tools able to address various synthesis and characterization challenges. These include the establishment and refinement of growth methods, material manipulation, and defect engineering. Material modification at the atomic level will be a key enabling factor for the engineering of quantum materials where desired phenomena are critically determined by local atomic structures. Successful use of scanning transmission electron microscopes (STEMs) for atomic scale material manipulation has opened the door for a transformed view of what can be accomplished using electron-beam-based strategies. However, serious obstacles exist on the pathway from possibility to practical reality. One such obstacle is the in situ delivery of atomized material in the STEM to the region of interest for further fabrication processes. Here, we present progress on this front with a view toward performing synthesis (deposition and growth) processes in a scanning transmission electron microscope. An in situ thermal deposition platform is presented, tested, and deposition and growth processes are demonstrated. In particular, we show that isolated Sn atoms can be evaporated from a filament and caught on the nearby sample, demonstrating atomized material delivery. This platform, and future variations, are envisioned to facilitate real-time atomic resolution imaging of growth processes and open new pathways toward atomic fabrication.

cond-mat.mtrl-sci↗

Top-down fabrication of atomic patterns in twisted bilayer graphene

Atomic-scale engineering typically involves bottom-up approaches, leveraging parameters such as temperature, partial pressures, and chemical affinity to promote spontaneous arrangement of atoms. These parameters are applied globally, resulting in atomic scale features scattered probabilistically throughout the material. In a top-down approach, different regions of the material are exposed to different parameters resulting in structural changes varying on the scale of the resolution. In this work, we combine the application of global and local parameters in an aberration corrected scanning transmission electron microscope (STEM) to demonstrate atomic scale precision patterning of atoms in twisted bilayer graphene. The focused electron beam is used to define attachment points for foreign atoms through the controlled ejection of carbon atoms from the graphene lattice. The sample environment is staged with nearby source materials, such that the sample temperature can induce migration of the source atoms across the sample surface. Under these conditions, the electron-beam (top-down) enables carbon atoms in the graphene to be replaced spontaneously by diffusing adatoms (bottom-up). Using image-based feedback-control, arbitrary patterns of atoms and atom clusters are attached to the twisted bilayer graphene with limited human interaction. The role of substrate temperature on adatom and vacancy diffusion is explored by first-principles simulations.

cond-mat.mtrl-sci↗

Direct Imaging of Electron Orbitals with a Scanning Transmission Electron Microscope

Recent studies of secondary electron (SE) emission in scanning transmission electron microscopes suggest that material's properties such as electrical conductivity, connectivity, and work function can be probed with atomic scale resolution using a technique known as secondary electron e-beam-induced current (SEEBIC). Here, we apply the SEEBIC imaging technique to a stacked 2D heterostructure device to reveal the spatially resolved electron orbital ionization cross section of an encapsulated WSe2 layer. We find that the double Se lattice site shows higher emission than the W site, which is at odds with first-principles modelling of ionization of an isolated WSe2 cluster. These results illustrate that atomic level SEEBIC contrast within a single material is possible and that an enhanced understanding of atomic scale SE emission is required to account for the observed contrast. In turn, this suggests that subtle information about interlayer bonding and the effect on electron orbitals can be directly revealed with this technique.

cond-mat.mtrl-sci↗

Probing temperature-induced phase transitions at individual ferroelectric domain walls

Ferroelectric domain walls have emerged as one of the most fascinating objects in condensed matter physics due to the broad variability of functional behaviors they exhibit. However, the vast majority of domain walls studies have been focused on bias-induced dynamics and transport behaviors. Here, we introduce the scanning probe microscopy approach based on piezoresponse force microscopy (PFM) with a dynamically heated probe, combining local heating and local biasing of the material. This approach is used to explore the thermal polarization dynamics in soft Sn2P2S6 ferroelectrics, and allows for the exploration of phase transitions at individual domain walls. The strong and weak modulation regimes for the thermal PFM are introduced. The future potential applications of heated probe approach for functional SPM measurements including piezoelectric, elastic, microwave, and transport measurements are discussed.

cond-mat.mtrl-sci↗

Mapping Conductance and Switching Behavior of Graphene Devices In Situ

Graphene has been proposed for use in various nanodevice designs, many of which harness emergent quantum properties for device functionality. However, visualization, measurement, and manipulation become non-trivial at nanometer and atomic scales, representing a significant challenge for device fabrication, characterization, and optimization at length scales where quantum effects emerge. Here, we present proof of principle results at the crossroads between 2D nanoelectronic devices, e-beam-induced modulation, and imaging with secondary electron e-beam induced currents (SEEBIC). We introduce a device platform compatible with scanning transmission electron microscopy investigations. We then show how the SEEBIC imaging technique can be used to visualize conductance and connectivity in single layer graphene nanodevices, even while supported on a thicker substrate (conditions under which conventional imaging fails). Finally, we show that the SEEBIC imaging technique can detect subtle differences in charge transport through time in non-ohmic graphene nanoconstrictions indicating the potential to reveal dynamic electronic processes.

cond-mat.mes-hall↗

Electron-beam Introduction of Heteroatomic Pt-Si Structures in Graphene

Electron-beam (e-beam) manipulation of single dopant atoms in an aberration-corrected scanning transmission electron microscope is emerging as a method for directed atomic motion and atom-by-atom assembly. Until now, the dopant species have been limited to atoms closely matched to carbon in terms of ionic radius and capable of strong covalent bonding with carbon atoms in the graphene lattice. In situ dopant insertion into a graphene lattice has thus far been demonstrated only for Si, which is ubiquitously present as a contaminant in this material. Here, we achieve in situ manipulation of Pt atoms and their insertion into the graphene host matrix using the e-beam deposited Pt on graphene as a host system. We further demonstrate a mechanism for stabilization of the Pt atom, enabled through the formation of Si-stabilized Pt heteroatomic clusters attached to the graphene surface. This study provides evidence toward the universality of the e-beam assembly approach, opening a pathway for exploring cluster chemistry through direct assembly.

cond-mat.mtrl-sci↗

Contrast mechanisms in secondary electron e-beam induced current (SEEBIC) imaging

Over the last few years, a new mode for imaging in the scanning transmission electron microscope (STEM) has gained attention as it permits the direct visualization of sample conductivity and electrical connectivity. When the electron beam (e-beam) is focused on the sample in the STEM, secondary electrons (SEs) are generated. If the sample is conductive and electrically connected to an amplifier, the SE current can be measured as a function of the e-beam position. This scenario is similar to the better-known scanning electron microscopy (SEM)-based technique, electron beam induced current (EBIC) imaging except the signal in STEM is generated by the emission of SEs, hence the name SEEBIC, and in this case the current flows in the opposite direction. Here, we provide a brief review of recent work in this area, examine the various contrast generation mechanisms associated with SEEBIC, and illustrate its use for the characterization of graphene nanoribbon devices.

cond-mat.mtrl-sci↗

Autonomous Experiments in Scanning Probe Microscopy and Spectroscopy: Choosing Where to Explore Polarization Dynamics in Ferroelectrics

Polarization dynamics in ferroelectric materials are explored via the automated experiment in Piezoresponse Force Spectroscopy. A Bayesian Optimization framework for imaging is developed and its performance for a variety of acquisition and pathfinding functions is explored using previously acquired data. The optimized algorithm is then deployed on an operational scanning probe microscope (SPM) for finding areas of large electromechanical response in a thin film of PbTiO3, with metrics showing gains of ~3x in the sampling efficiency. This approach opens the pathway to perform more complex spectroscopies in SPM that were previously not possible due to time constraints and sample stability, tip wear, and/or stochastic sample damage that occurs at specific, a priori unknown spatial positions. Potential improvements to the framework to enable the incorporation of more prior information and improve efficiency further are discussed.

cond-mat.dis-nn↗

Exploring order parameters and dynamic processes in disordered systems via variational autoencoders

We suggest and implement an approach for the bottom-up description of systems undergoing large-scale structural changes and chemical transformations from dynamic atomically resolved imaging data, where only partial or uncertain data on atomic positions are available. This approach is predicated on the synergy of two concepts, the parsimony of physical descriptors and general rotational invariance of non-crystalline solids, and is implemented using a rotationally-invariant extension of the variational autoencoder applied to semantically segmented atom-resolved data seeking the most effective reduced representation for the system that still contains the maximum amount of original information. This approach allowed us to explore the dynamic evolution of electron beam-induced processes in a silicon-doped graphene system, but it can be also applied for a much broader range of atomic-scale and mesoscopic phenomena to introduce the bottom-up order parameters and explore their dynamics with time and in response to external stimuli.

cond-mat.mtrl-sci↗

Van der Waals Epitaxy on Freestanding Monolayer Graphene Membrane by MBE

Research on two-dimensional materials has expanded over the past two decades to become a central theme in condensed matter research today. Significant advances have been made in the synthesis and subsequent reassembly of these materials using mechanical methods into a vast array of hybrid structures with novel properties and ever-increasing potential applications. The key hurdles in realizing this potential are the challenges in controlling the atomic structure of these layered hybrid materials and the difficulties in harnessing their unique functionality with existing semiconductor nanofabrication techniques. Here we report on high-quality van der Waals epitaxial growth and characterization of a layered topological insulator on freestanding monolayer graphene transferred to different mechanical supports. This templated synthesis approach enables direct interrogation of interfacial atomic structure of these as-grown hybrid structures and opens a route towards creating device structures with more traditional semiconductor nanofabrication techniques.

cond-mat.mtrl-sci↗

Automated and Autonomous Experiment in Electron and Scanning Probe Microscopy

Machine learning and artificial intelligence (ML/AI) are rapidly becoming an indispensable part of physics research, with domain applications ranging from theory and materials prediction to high-throughput data analysis. In parallel, the recent successes in applying ML/AI methods for autonomous systems from robotics through self-driving cars to organic and inorganic synthesis are generating enthusiasm for the potential of these techniques to enable automated and autonomous experiment (AE) in imaging. Here, we aim to analyze the major pathways towards AE in imaging methods with sequential image formation mechanisms, focusing on scanning probe microscopy (SPM) and (scanning) transmission electron microscopy ((S)TEM). We argue that automated experiments should necessarily be discussed in a broader context of the general domain knowledge that both informs the experiment and is increased as the result of the experiment. As such, this analysis should explore the human and ML/AI roles prior to and during the experiment, and consider the latencies, biases, and knowledge priors of the decision-making process. Similarly, such discussion should include the limitations of the existing imaging systems, including intrinsic latencies, non-idealities and drifts comprising both correctable and stochastic components. We further pose that the role of the AE in microscopy is not the exclusion of human operators (as is the case for autonomous driving), but rather automation of routine operations such as microscope tuning, etc., prior to the experiment, and conversion of low latency decision making processes on the time scale spanning from image acquisition to human-level high-order experiment planning.

cs.LG↗