Engineering Papers⌕ Search

Engineering topics

Jesse, Stephen

Publications and source records attributed to Jesse, Stephen.

At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Compressed Sensing of Scanning Transmission Electron Microscopy (STEM) With Nonrectangular Scans

Scanning transmission electron microscopy (STEM) has become the main stay for materials characterization on atomic level, with applications ranging from visualization of localized and extended defects to mapping order parameter fields. In recent years, attention has focused on the potential of STEM to explore beam induced chemical processes and especially manipulating atomic motion, enabling atom-by-atom fabrication. These applications, as well as traditional imaging of beam sensitive materials, necessitate increasing the dynamic range of STEM in imaging and manipulation modes, and increasing the absolute scanning speed which can be achieved by combining sparse sensing methods with nonrectangular scanning trajectories. We have developed a general method for real-time reconstruction of sparsely sampled images from high-speed, noninvasive and diverse scanning pathways, including spiral scan and Lissajous scan. This approach is demonstrated on both the synthetic data and experimental STEM data on the beam sensitive material graphene. This work opens the door for comprehensive investigation and optimal design of dose efficient scanning strategies and real-time adaptive inference and control of e-beam induced atomic fabrication.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Decoupling Mesoscale Functional Response in PLZT across the Ferroelectric–Relaxor Phase Transition with Contact Kelvin Probe Force Microscopy and Machine Learning

Relaxor ferroelectrics exhibit a range of interesting material behavior, including high electromechanical response, polarization rotations, as well as temperature and electric field-driven phase transitions. The origin of this unusual functional behavior remains elusive due to limited knowledge on polarization dynamics at the nanoscale. Piezoresponse force microscopy and associated switching spectroscopy provide access to local electromechanical properties on the micro- and nanoscale, which can help to address some of these gaps in our knowledge. However, these techniques are inherently prone to artefacts caused by signal contributions emanating from electrostatic interactions between tip and sample. Understanding functional behavior of complex, disordered systems like relaxor materials with unknown electromechanical properties therefore requires a technique that allows distinguishing between electromechanical and electrostatic response. Here, contact Kelvin probe force microscopy (cKPFM) is used to gain insight into the evolution of local electromechanical and capacitive properties of a representative relaxor material lead lanthanum zirconate across the phase transition from a ferroelectric to relaxor state. The obtained multidimensional data set was processed using an unsupervised machine learning algorithm to detect variations in functional response across the probed area and temperature range. Further analysis showed the formation of two separate cKPFM response bands below 50 °C, providing evidence for polarization switching. At higher temperatures only one band is observed, indicating an electrostatic origin of the measured response. In addition, the junction potential difference, which was extracted from the cKPFM data, becomes independent of the temperature in the relaxor state. As a result, the combination of this multidimensional voltage spectroscopy technique and machine learning allows to identify the origin of the measured functional response and to decouple ferroelectric from electrostatic phenomena necessary to understand the functional behavior of complex, disordered systems like relaxor materials.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Theory-assisted determination of nano-rippling and impurities in atomic resolution images of angle-mismatched bilayer graphene

Ripples and impurity atoms are universally present in 2D materials, limiting carrier mobility, creating pseudo–magnetic fields, or affecting the electronic and magnetic properties. Scanning transmission electron microscopy (STEM) generally provides picometer-level precision in the determination of the location of atoms or atomic 'columns' in the in-image plane (xy plane). However, precise atomic positions in the z-direction as well as the presence of certain impurities are difficult to detect. Furthermore, images containing moiré patterns such as those in angle-mismatched bilayer graphene compound the problem by limiting the determination of atomic positions in the xy plane. Here, we introduce a reconstructive approach for the analysis of STEM images of twisted bilayers that combines the accessible xy coordinates of atomic positions in a STEM image with density-functional-theory calculations. The approach allows us to determine all three coordinates of all atomic positions in the bilayer and establishes the presence and identity of impurities. In this work, the deduced strain-induced rippling in a twisted bilayer graphene sample is consistent with the continuum model of elasticity. We also find that the moiré pattern induces undulations in the z direction that are approximately an order of magnitude smaller than the strain-induced rippling. A single substitutional impurity, identified as nitrogen, is detected. The present reconstructive approach can, therefore, distinguish between moiré and strain-induced effects and allows for the full reconstruction of 3D positions and atomic identities.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Time resolved surface photovoltage measurements using a big data capture approach to KPFM

Optoelectronic behavior in materials such as organic/inorganic hybrid perovskites depend on a complex interplay between fast (electronic) and slower (ionic) processes. These processes are thought to be influenced by structural inhomogeneities (e.g. interfaces and grain boundaries) bringing forward the necessity for development of techniques capable of correlating nanostructure and photo-transport behavior. While Kelvin probe force microscopy (KPFM) is ideally suited to map surface potentials on relevant length scales, it lacks sufficient temporal resolution to extract the meaningful system dynamics. Here, we develop a time resolved surface photovoltage (SPV) measurement based on full information capture of the photodetector stream during open loop KPFM operation. G-Mode, or G-KPFM allows quantification of SPV with microsecond temporal and nanoscale spatial resolution. Using this technique, we observe concurrent spatial and fast temporal variations in the SPV generated across a methylammonium lead bromide (MAPbBr3) thin film, a possible indicator relating microstructure with heterogenous photo-transport behavior. Here, we further demonstrate the advantage of adopting big data analytics including unsupervised clustering methods to quickly discern spatial variability in the information rich SPV dataset. Beyond G-KPFM, such clustering methods will be useful for interpretation of the multidimensional datasets arising from the growing number of time resolved KPFM approaches now available.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Chemical nature of ferroelastic twin domains in CH 3 NH 3 PbI 3 perovskite

The extraordinary optoelectronic performance of hybrid organic–inorganic perovskites has resulted in extensive efforts to unravel their properties. Recently, observations of ferroic twin domains in methylammonium lead triiodide drew significant attention as a possible explanation for the current–voltage hysteretic behaviour in these materials. However, the properties of the twin domains, their local chemistry and the chemical impact on optoelectronic performance remain unclear. Here, using multimodal chemical and functional imaging methods, we unveil the mechanical origin of the twin domain contrast observed with piezoresponse force microscopy in methylammonium lead triiodide. By combining experimental results with first principles simulations we reveal an inherent coupling between ferroelastic twin domains and chemical segregation. Furthermore, these results reveal an interplay of ferroic properties and chemical segregation on the optoelectronic performance of hybrid organic–inorganic perovskites, and offer an exploratory path to improving functional devices.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Building Structures Atom by Atom via Electron Beam Manipulation

Building materials from the atom up is the pinnacle of materials fabrication. Until recently the only platform that offered single-atom manipulation was scanning tunneling microscopy. Here controlled manipulation and assembly of a few atom structures are demonstrated by bringing together single atoms using a scanning transmission electron microscope. An atomically focused electron beam is used to introduce Si substitutional defects and defect clusters in graphene with spatial control of a few nanometers and enable controlled motion of Si atoms. The Si substitutional defects are then further manipulated to form dimers, trimers, and more complex structures. The dynamics of a beam-induced atomic-scale chemical process is captured in a time-series of images at atomic resolution. In conclusion, these studies suggest that control of the e-beam-induced local processes offers the next step toward atom-by-atom nanofabrication, providing an enabling tool for the study of atomic-scale chemistry in 2D materials and fabrication of predefined structures and defects with atomic specificity.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Dynamic behavior of CH 3 NH 3 PbI 3 perovskite twin domains

We report the recent discovery of twin domains in MAPbI 3 perovskites has initiated contentious discussion on the ferroic nature of hybrid perovskites. Ferroelectric polarization is thought to facilitate the dissociation of photoinduced electron-hole pairs, helping to explain the extraordinary photovoltaic performance exhibited by this class of materials. Alternate to ferroelectricity, which has yet to be unambiguously established despite considerable efforts to do so, ferroelasticity was also proposed in these materials. Meanwhile, given the coupling of ionic states and ferroelectricity and the interconnected nature of defect chemistry and ferroelasticity, the electrochemical reactivity can no longer be ignored. In this work, using band excitation piezoresponse force microscopy, we reveal the variation in elasticity between adjacent domains, indicating the ferroelasticity and the difference in the crystallographic states of the twin domain. Moreover, using band excitation contact Kelvin probe force microscopy, we dynamically map the evolution of the twinning structure under electric bias. These results help decipher the effect of the twin domains on ionic mobility and ion diffusion pathways. Combining these results, we reveal the interaction of twin domains and ionic activity in this material. Furthermore, this work provides insights into the twinning structure in MAPbI 3 and its potential effects on the hybrid perovskite optoelectronics.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Surface Chemistry Controls Anomalous Ferroelectric Behavior in Lithium Niobate

Polarization switching in ferroelectric materials underpins a multitude of applications ranging from nonvolatile memories to data storage to ferroelectric lithography. While traditionally considered to be a functionality of the material only, basic theoretical considerations suggest that switching is expected to be intrinsically linked to changes in the electrochemical state of the surface. Hence, the properties and dynamics of the screening charges can affect or control the switching dynamics. Despite being recognized for over 50 years, analysis of these phenomena remained largely speculative. Here, we explore polarization switching on the prototypical LiNbO 3 surface using the combination of contact mode Kelvin probe force microscopy and chemical imaging by time-of-flight mass-spectrometry and demonstrate pronounced chemical differences between the domains. Here, these studies provide a consistent explanation to the anomalous polarization and surface charge behavior observed in LiNbO 3 and point to new opportunities in chemical control of polarization dynamics in thin films and crystals via control of surface chemistry, complementing traditional routes via bulk doping, and substrate-induced strain and tilt systems.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Locally Controlled Cu-Ion Transport in Layered Ferroelectric CuInP 2 S 6

Metal thiophosphates are gaining attention in the context of quasi-two-dimensional van der Waals functional materials. Alkali thiophosphates are investigated as ion conductors for solid electrolytes, and transition-metal thiophosphates are explored as a new class of ferroelectric materials. For the latter, a representative copper indium thiophosphate is ferrielectric at room temperature and, despite low polarization, exhibits giant negative electrostrictive coefficients. In this work, we reveal that ionic conductivity in this material enables localized extraction of Cu ions from the lattice with a biased scanning probe microscopy tip, which is surprisingly reversible. The ionic conduction is tracked through local volume changes with a scanning probe microscopy tip providing a current-free probing technique, which can be explored for other thiophosphates of interest. Nearly 90 nm-tall crystallites can be formed and erased reversibly on the surface of this material as a result of ionic motion, the size of which can be sensitively controlled by both magnitude and frequency of the electric field, as well as the ambient temperature. These experimental results and density functional theory calculations point to a remarkable resilience of CuInP 2 S 6 to large-scale ionic displacement and Cu vacancies, in part enabled by the metastability of Cu-deficient phases. Moreover, we have found that the piezoelectric response of CuInP 2 S 6 is enhanced by about 45% when a slight ionic modification is carried out with applied field. This new mode of modifying the lattice of CuInP 2 S 6 , and more generally ionically conducting thiophosphates, posits new prospects for their applications in van der Waals heterostructures, possibly in the context of catalytic or electronic functionalities.

36 MATERIALS SCIENCE↗
DOE OSTI2018

E-beam manipulation of Si atoms on graphene edges with an aberration-corrected scanning transmission electron microscope

The burgeoning field of atomic-level material control holds great promise for future breakthroughs in quantum and memristive device manufacture and fundamental studies of atomic-scale chemistry. Realization of atom-by-atom control of matter represents a complex and ongoing challenge. Here, we explore the feasibility of controllable motion of dopant Si atoms at the edges of graphene via the sub-atomically focused electron beam in a scanning transmission electron microscope. Furthermore, we demonstrate that the graphene edges can be cleaned of Si atoms and then subsequently replenished from nearby source material. It is also shown how Si edge atoms may be “pushed” from the edge of a small hole into the bulk of the graphene lattice and from the bulk of the lattice back to the edge. This is accomplished through sputtering of the edge of the graphene lattice to bury or uncover Si dopant atoms. Finally, we demonstrate e-beam mediated hole healing and incorporation of dopant atoms. These experiments form an initial step toward general atomic-scale material control.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2018

High-veracity functional imaging in scanning probe microscopy via Graph-Bootstrapping

The key objective of scanning probe microscopy (SPM) techniques is the optimal representation of the nanoscale surface structure and functionality inferred from the dynamics of the cantilever. This is particularly pertinent today, as the SPM community has seen a rapidly growing trend towards simultaneous capture of multiple imaging channels and complex modes of operation involving high-dimensional information-rich datasets, bringing forward the challenges of visualization and analysis, particularly for cases where the underlying dynamic model is poorly understood. To meet this challenge, we present a data-driven approach, Graph-Bootstrapping, based on low-dimensional manifold learning of the full SPM spectra and demonstrate its successes for high-veracity mechanical mapping on a mixed polymer thin film and resolving irregular hydration structure of calcite at atomic resolution. Using the proposed methodology, we can efficiently reveal and hierarchically represent salient material features with rich local details, further enabling denoising, classification, and high-resolution functional imaging.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Graphene milling dynamics during helium ion beam irradiation

We explore the potential of the Helium Ion Microscope (HIM) as a tool for direct-write patterning of graphene and describe the underlying processes of graphene milling with image data processing. Controlled helium ion irradiation of suspended graphene conducted while monitoring the mill in-situ revealed the localized formation of nanopores, their growth, and coalescence. We also explore the effects of defects on the milling dynamics, and show that pre-exposed membranes rupture by cracking and rapid crack propagation at the edges of the growing defects. The mechanism for the rupturing process is described by local defect formation by excessive irradiation of helium ions, dictated by the scanning direction of the beam. As a result, these findings enrich fundamental understanding of the graphene milling process with a helium ion beam that, is necessary for high-resolution and high throughput patterning of graphene with nanoscale precision.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Machine Detection of Enhanced Electromechanical Energy Conversion in PbZr 0.2 Ti 0.8 O 3 Thin Films

Many energy conversion, sensing, and microelectronic applications based on ferroic materials are determined by the domain structure evolution under applied stimuli. New hyperspectral, multidimensional spectroscopic techniques now probe dynamic responses at relevant length and time scales to provide an understanding of how these nanoscale domain structures impact macroscopic properties. Such approaches, however, remain limited in use because of the difficulties that exist in extracting and visualizing scientific insights from these complex datasets. Using multidimensional band-excitation scanning probe spectroscopy and adapting tools from both computer vision and machine learning, an automated workflow is developed to featurize, detect, and classify signatures of ferroelectric/ferroelastic switching processes in complex ferroelectric domain structures. This approach enables the identification and nanoscale visualization of varied modes of response and a pathway to statistically meaningful quantification of the differences between those modes. Lastly, among other things, the importance of domain geometry is spatially visualized for enhancing nanoscale electromechanical energy conversion.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Direct atomic fabrication and dopant positioning in Si using electron beams with active real-time image-based feedback

We report that semiconductor fabrication is a mainstay of modern civilization, enabling the myriad applications and technologies that underpin everyday life. However, while sub-10 nanometer devices are already entering the mainstream, the end of the Moore's law roadmap still lacks tools capable of bulk semiconductor fabrication on sub-nanometer and atomic levels, with probe-based manipulation being explored as the only known pathway. Here we demonstrate that the atomic-sized focused beam of a scanning transmission electron microscope can be used to manipulate semiconductors such as Si on the atomic level, inducing growth of crystalline Si from the amorphous phase, reentrant amorphization, milling, and dopant front motion. These phenomena are visualized in real-time with atomic resolution. We further implement active feedback control based on real-time image analytics to automatically control the e-beam motion, enabling shape control and providing a pathway for atom-by-atom correction of fabricated structures in the near future. Lastly, these observations open a new epoch for atom-by-atom manufacturing in bulk, the long-held dream of nanotechnology.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Machine learning–enabled identification of material phase transitions based on experimental data: Exploring collective dynamics in ferroelectric relaxors

Exploration of phase transitions and construction of associated phase diagrams are of fundamental importance for condensed matter physics and materials science alike, and remain the focus of extensive research for both theoretical and experimental studies. For the latter, comprehensive studies involving scattering, thermodynamics, and modeling are typically required. We present a new approach to data mining multiple realizations of collective dynamics, measured through piezoelectric relaxation studies, to identify the onset of a structural phase transition in nanometer-scale volumes, that is, the probed volume of an atomic force microscope tip. Machine learning is used to analyze the multidimensional data sets describing relaxation to voltage and thermal stimuli, producing the temperature-bias phase diagram for a relaxor crystal without the need to measure (or know) the order parameter. The suitability of the approach to determine the phase diagram is shown with simulations based on a two-dimensional Ising model. Finally, these results indicate that machine learning approaches can be used to determine phase transitions in ferroelectrics, providing a general, statistically significant, and robust approach toward determining the presence of critical regimes and phase boundaries.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Two-level structural sparsity regularization for identifying lattices and defects in noisy images

Here, this paper presents a regularized regression model with a two-level structural sparsity penalty applied to locate individual atoms in a noisy scanning transmission electron microscopy image (STEM). In crystals, the locations of atoms is symmetric, condensed into a few lattice groups. Therefore, by identifying the underlying lattice in a given image, individual atoms can be accurately located. We propose to formulate the identification of the lattice groups as a sparse group selection problem. Furthermore, real atomic scale images contain defects and vacancies, so atomic identification based solely on a lattice group may result in false positives and false negatives. To minimize error, model includes an individual sparsity regularization in addition to the group sparsity for a within-group selection, which results in a regression model with a two-level sparsity regularization. We propose a modification of the group orthogonal matching pursuit (gOMP) algorithm with a thresholding step to solve the atom finding problem. The convergence and statistical analyses of the proposed algorithm are presented. The proposed algorithm is also evaluated through numerical experiments with simulated images. The applicability of the algorithm on determination of atom structures and identification of imaging distortions and atomic defects was demonstrated using three real STEM images. In conclusion, we believe this is an important step toward automatic phase identification and assignment with the advent of genomic databases for materials.

36 MATERIALS SCIENCE↗