Multidimensional, experimental and modeling evaluation of permeability evolution, the Caney Shale Field Lab, OK, USA
Multidimensional, experimental and modeling evaluation of permeability evolution, the Caney Shale Field Lab, OK, USA
Katende, A.↗
SEARCH · Engineering Papers
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Leveraging unlabeled SEM datasets with self-supervised learning for enhanced particle segmentation
Scanning Electron Microscopes (SEMs) are widely used in experimental science laboratories, often requiring cumbersome and repetitive user analysis. Automating SEM image analysis processes is highly desirable to address this challenge. In particle sample analysis, Machine Learning (ML) has emerged as the most effective approach for particle segmentation. However, the time-intensive process of manually annotating thousands of SEM images limits the applicability of supervised learning approaches. Self-Supervised Learning (SSL) offers a promising alternative by enabling knowledge extraction from raw, unlabeled data. This study presents a framework for evaluating SSL techniques in SEM image analysis, focusing on novel methods leveraging the ConvNeXtV2 architecture for particle detection. A dataset comprising 25,000 SEM images is curated to benchmark these proposed SSL methods. The results demonstrate that ConvNeXtV2 models, with varying parameter counts, consistently outperform other techniques in particle detection across different length scales, achieving up to a 34% reduction in relative error compared to established SSL methods. Furthermore, an ablation study explores the relationship between dataset size and SSL performance, providing actionable insights for practitioners regarding model selection and resource efficiency. This research advances the integration of SSL into autonomous analysis pipelines and supports its application in accelerating materials science discovery.
Rettenberger, Luca↗
Wavelength domain spatial frequency modulation imaging: enabling fiber optic delivery and detection
Spatial frequency modulation imaging (SPIFI) provides a simple architecture for modulating an extended illumination source that is compatible with single pixel imaging. We demonstrate wavelength domain SPIFI (WD-SPIFI) by encoding time-varying spatial frequencies in the spectral domain that can produce enhanced resolution images, like its spatial domain counterpart, spatial domain (SD) SPIFI. However, contrary to SD-SPIFI, WD-SPIFI enables remote delivery by single mode fiber, which can be attractive for applications where free-space imaging is not practical. Finally, we demonstrate a cascaded system incorporating WD-SPIFI in-line with SD-SPIFI enabling single pixel 2D imaging without any beam or sample scanning.
47 OTHER INSTRUMENTATION↗
Revealing Phase Heterogeneity in Vertically Aligned Nanocomposites via Plan-View Electron Energy Loss Spectroscopy
Hydrogen utilization in clean energy technologies is challenged by limited storage and transport within materials, owing to the complex hydrogen kinetics at interfaces [1]. Understanding these interfacial mechanisms at the nanoscale is crucial for developing improved materials for hydrogen applications, particularly proton-conducting fuel cells (PCFCs). Vertically aligned nanocomposites (VANs) grown by pulsed laser deposition (PLD) offer a unique platform for investigating the interfacial effects on hydrogen transport due to their well-defined interfaces parallel to the direction of charge transport [2-4]. To investigate hydrogen transport, the two phases within the VANs were chosen as BaZr 0.9 Y 0.1 O 3-x (BZY), a known proton conductor, and Pr 0.1 Ce 0.9 O 2-x (PCO), a mixed ionic-electronic conductor [5]. This PCO-BZY VANs architecture allows the investigation of how the interface between a proton conductor and a mixed conductor influences hydrogen transport. However, because of the small size of hydrogen, it is difficult to discern the nature of its interactions with interfaces from bulk measurements at the macroscale, thus necessitating nanoscale measurements [6]. Electron energy loss spectroscopy (EELS) allows for nanometer-resolution probing of the local atomic structure and chemistry at the BZY/PCO interface. In this study, plan-view analysis of PCO-BZY VANs films was employed to characterize the structure and phase distribution of the VANs and investigate the interface between the nanostructures. The films were imaged using scanning electron microscopy (SEM) in the Hitachi S-4800 SEM, collecting secondary electron images using mixed upper and lower detectors. Then, plan-view transmission electron microscopy (TEM) and scanning transmission electron microscopy (STEM) EELS were employed using a JEOL ARM300 microscope operated at 300kV with a Gatan K3 GIF Continuum detector to study the distribution of the BZY and PCO phases through the film. As a result, spectrum images were acquired at a dispersion of 0.18eV per channel and denoised afterward by principal component analysis (PCA) method.
Griffin, Elizabeth [Northwestern University, Evans↗
Thermal Transport and Mechanical Stress Mapping of a Compression Bonded GaN/Diamond Interface for Vertical Power Devices
Bonding diamond to the back side of gallium nitride (GaN) electronics has been shown to improve thermal management in lateral devices; however, engineering challenges remain with the bonding process and characterizing the bond quality for vertical device architectures. Here, in this study, integration of these two materials is achieved by room-temperature compression bonding centimeter-scale GaN and a diamond die via an intermetallic bonding layer of Ti/Au. Recent attempts at GaN/diamond bonding have utilized a modified surface activation bonding (SAB) method, which requires Ar fast atom bombardment immediately followed by bonding within the same tool under ultrahigh vacuum (UHV) conditions. The method presented here does not require a dedicated SAB tool yet still achieves bonding via a room-temperature metal–metal compression process. Imaging of the buried interface and the total bonding area is achieved via transmission electron microscopy (TEM) and confocal acoustic scanning microscopy (C-SAM), respectively. The thermal transport quality of the bond is extracted from spatially resolved frequency-domain thermoreflectance (FDTR) with the bonded areas boasting a thermal boundary conductance of >100 MW/m 2 ·K. Additionally, Raman maps of GaN near the GaN–diamond interface reveal a low level of compressive stress, <80 MPa, in well-bonded regions. FDTR and Raman were coutilized to map these buried interfaces and revealed some poor thermally bonded areas bordered by high-stress regions, highlighting the importance of spatial sampling for a complete picture of bond quality. Overall, this work demonstrates a novel method for thermal management in vertical GaN devices that maintains low intrinsic stresses while boasting high thermal boundary conductances.
Raman↗
In situ energetics modulation enables high-efficiency and stable inverted perovskite solar cells
In contrast to conventional (n-i-p) perovskite solar cells (PSCs), inverted (p-i-n) PSCs offer enhanced stability and integrability with tandem solar cell architectures, which have garnered increasing interest. However, p-i-n cells suffer from energy level misalignment with transport layers, imbalanced transport of photo-generated electrons and holes, and significant defects with the perovskite films. Here we introduce tris(2,4,6-trimethyl-3-(pyridin-3-yl)phenyl)borane (3TPYMB), a nonionic n-type molecule that, through hydrogen bonding and Lewis acid-base reactions with perovskite surfaces or grain boundaries, enables in situ modulation of perovskite energetics, effectively mitigating the key challenges of p-i-n PSCs. The p-i-n PSCs incorporating 3TPYMB achieve a certified quasi-steady-state power conversion efficiency of 24.55 +- 0.33%, with a reverse scan efficiency of 25.58%. Finally, they also exhibit exceptional stability, with unencapsulated devices retaining 97.8% of their initial efficiency after 1,800 h of continuous operation at maximum power point under N 2 atmosphere, 1 sun illumination and 60 °C conditions.
14 SOLAR ENERGY↗
Characterization of an architecture for front-end pixel binning in an integrating pixel array detector
Optimization of an area detector involves compromises between various parameters like frame rate, read noise, dynamic range and pixel size. We have implemented and tested a novel front-end binning design in a photon-integrating hybrid pixel array detector using the MM-PAD- 2.0 pixel architecture. In this architecture, the pixels can be optionally binned in a 2 x 2 pixel configuration using a network of switches to selectively direct the output of 4 sensor pixels to a single amplifier input. Doing this allows a trade-off between frame rate and spatial resolution. Tests show that the binned pixels perform well, but with some degradation on performance as compared to an un-binned pixel. The increased parasitic input capacitance does reduce the signal collected per x-ray as well as increases the noise of the pixel. Here, the increase in noise is, however, less than the factor of 2 increase one would observe for binning in post-processing. Spatial scans across the binned pixels show that no measured signal intensity is lost at the inner binning unit boundaries. In the high flux regime, at a 2 x 2 pixel wide beam spot (FWHM) size, binned mode responds linearly up to a photon flux of 10 7 x-rays/s, and performs comparably with un-binned mode up to a photon flux of 10 8 x-rays/s. While this study demonstrates a proof of concept for front-end binning in integrating detectors, we also identify changes to this early-stage prototype which can further improve the performance of binning pixel structures.
47 OTHER INSTRUMENTATION↗
Automatic point Cloud Building Envelope Segmentation (Auto-CuBES) using Machine Learning
Modern retrofit construction practices use 3D point cloud data of the building envelope to obtain the as-built dimensions. However, manual segmentation by a trained professional is required to identify and measure window openings, door openings, and other architectural features, making the use of 3D point clouds labor-intensive. In this study, the Automatic point Cloud Building Envelope Segmentation (Auto-CuBES) algorithm is described, which can significantly reduce the time spent during point cloud segmentation. The Auto-CuBES algorithm inputs a 3D point cloud generated by commonly available surveying equipment and outputs a wire-frame model of the building envelope. Unsupervised machine learning methods were used to identify facades, windows, and doors while minimizing the number of calibration parameters. Additionally, Auto-CuBES generates a heat map of each facade indicating non-planar characteristics that are crucial for the optimization of connections used in overclad envelope retrofits. With a scan resolution of 3 mm, the resulting window dimensions showed a mean absolute error of 4.2 mm compared to manual laser measurements.
Maldonado Puente, Bryan↗
Distributed Stochastic Optimization of a Neural Representation Network for Time-Space Tomography Reconstruction
4D time-space reconstruction of dynamic events or deforming objects using X-ray computed tomography (CT) is an important inverse problem in non-destructive evaluation. Conventional back-projection based reconstruction methods assume that the object remains static for the duration of several tens or hundreds of X-ray projection measurement images (reconstruction of consecutive limited-angle CT scans). However, this is an unrealistic assumption for many in-situ experiments that causes spurious artifacts and inaccurate morphological reconstructions of the object. To solve this problem, we propose to perform a 4D time-space reconstruction using a distributed implicit neural representation (DINR) network that is trained using a novel distributed stochastic training algorithm. Our DINR network learns to reconstruct the object at its output by iterative optimization of its network parameters such that the measured projection images best match the output of the CT forward measurement model. Here, we use a forward measurement model that is a function of the DINR outputs at a sparsely sampled set of continuous valued 4D object coordinates. Unlike previous neural representation architectures that forward and back propagate through dense voxel grids that sample the object's entire time-space coordinates, we only propagate through the DINR at a small subset of object coordinates in each iteration resulting in an order-of-magnitude reduction in memory and compute for training. DINR leverages distributed computation across several compute nodes and GPUs to produce high-fidelity 4D time-space reconstructions. We use both simulated parallel-beam and experimental cone-beam X-ray CT datasets to demonstrate the superior performance of our approach.
36 MATERIALS SCIENCE↗
Plasma-Initiated Graft Polymerization of Acrylic Acid onto Fluorine-Doped Tin Oxide as a Platform for Immobilization of Water-Oxidation Catalysts
The discovery of new and versatile strategies for the immobilization of molecular water-oxidation catalysts (WOCs) is crucial for developing clean energy conversion devices [e.g., (photo)electrocatalytic cells for water splitting]. The traditional approach for surface attachment to transparent conductive oxides [e.g., fluorine doped tin oxide (FTO)] is via synthetic modification of the ligand architecture to incorporate functional groups such as carboxylic acids (-COOH) or phosphonates (-PO 3 H 2 ) prior to immobilization. However, challenges arising from desorption and the cumbersome derivatizations steps have limited the scope and applications of surface-bound WOCs. Herein, we report the successful immobilization of underivatized Ru(II)-based WOCs (Ru–Cat1 = [Ru(tpy) (bpy) (H 2 O)] 2+ (tpy = 2,2':6'2"–terpyridine and bpy = 2,2;-bipyridine) and Ru–Cat2 = [Ru(Mebimpy) (bpy) (H 2 O)] 2+ (Mebimpy = 2,6-bis(1-methylbenzimidazol-2-yl) pyridine)) and the Ru(II) polypyridyl chromophore Ru–C3 = [Ru(bpy) 3 ] 2+ onto a FTO plasma-grafted poly(acrylic acid) surface (PAA|FTO). Various characterization techniques such as attenuated total reflectance Fourier transform infrared spectroscopy, scanning electron microscopy, atomic force microscopy, and cyclic voltammetry measurements provide evidence for the plasma-induced grafted PAA|FTO film and immobilization. Surface stability and electrocatalytic properties of these new hybrid composite films upon cycling were investigated at different pH values. Immobilized Ru–Cat1 and Ru–Cat2 onto PAA|FTO displayed pH-dependent (RuIII/RuII) couples and onset potentials indicative of PCET (proton-coupled electron transfer) reactions. Based on cyclic voltammetry results and spectroscopic monitoring, the immobilized WOCs Ru–Cat1 and Ru–Cat2 exhibited a higher surface stability in neutral aqueous solutions relative to Ru–C3 upon electrochemical oxidation. Furthermore, we attribute the surface PCET and stability to the presence of a water ligand in the coordination sphere of immobilized Ru–Cat1 and Ru–Cat2 which can H-bond with negatively charged carboxylate groups of the cross-linked PAA brushes. Our findings demonstrate that the plasma-grafted polymeric network onto FTO offers a versatile platform to directly anchor unmodified homogeneous WOCs or chromophores for potential applications in solar-to-fuel energy conversion.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Plasma-Enhanced Atomic Layer Deposition Synthesis of Nanolayered Molybdenum Diselenide (MoSe 2 ) Thin Films for Nanoelectronics
Nanolayered molybdenum diselenide (MoSe 2 ) thin films were synthesized by plasma-enhanced atomic layer deposition (PE-ALD) using molybdenum pentachloride (MoCl 5 ) and diethyldiselenide (C 4 H 10 Se 2 ) precursors. Scanning and transmission electron microscopy revealed horizontally stacked nanolayers near the substrate and vertically oriented nanosheets at the surface of the film. X-ray diffraction confirmed the (002), (100), and (110) reflections of crystalline MoSe 2 , while X-ray photoelectron spectroscopy showed relative atomic concentrations of 33.5% Mo and 66.5% Se, consistent with stoichiometric MoSe 2 . Raman spectra exhibited characteristic E 1g , A 1g , and E$^1_{2g}$ vibrational modes. Field-effect transistors incorporating PE-ALD-grown MoSe 2 as the channel material displayed p-type behavior, demonstrating the potential of nanolayered MoSe 2 for nanoelectronic applications. This work demonstrates the feasibility of low-temperature, stoichiometric growth of nanolayered MoSe 2 by PE-ALD and its direct integration into transistor architectures.
36 MATERIALS SCIENCE↗
Carbon-Based Quantum Information Science with Symmetry Protected Topological States (Final Report, DOE-BES award DE-SC0023105)
This research program established the scientific foundation for the rational, bottom-up design, synthesis, isolation, and investigation of symmetry-protected topological (SPT) electron spin qubits embedded in graphene nanoribbons (GNRs). The work focused on integrating atomically precise low-dimensional carbon nanostructures with emerging quantum logic architectures, providing a pathway toward scalable quantum materials for next-generation computing and sensing technologies. A central component of the program was the elucidation of fundamental relationships between real-space molecular architecture, local spin density distributions, electronic band dispersion, and energy level alignment in atomically precise GNR systems. These correlations define key operational parameters of SPT qubits and were systematically investigated to establish quantitative benchmarks against established molecular and solid-state spin qubit platforms. Attention was given to properties critical for quantum device performance, e.g. decoherence times, spectral sharpness of energy transitions, and tunable exchange interactions between spin states. The research demonstrated that these parameters can be engineered with atomic precision through scalable bottom-up synthetic strategies. Theory-guided design played a central role in identifying candidate structures hosting topologically protected spin states. Experimental validation was performed using both ensemble measurements and single-molecule characterization. In addition to advances in quantum materials synthesis, the program developed and applied spin-sensitive scanning probe microscopy techniques capable of directly probing quantum states and dynamic processes with atomic-scale spatial resolution. These capabilities enabled direct observation and characterization of quantum structures at the single-atom level. While the research activities were primarily hypothesis-driven fundamental investigations, the program adopted a comprehensive materials-by-design framework aimed at translating scientific discoveries into technological concepts compatible with scalable and intelligent manufacturing approaches.
36 MATERIALS SCIENCE↗
Nanostructural and rheological transitions of pH-responsive supramolecular systems involving a zwitterionic amphiphile and a triamine
Supramolecular aqueous complexes of a synthesized zwitterionic surfactant, 2-(dimethyl(octadecyl)ammonio)acetate (stearyl betaine) and diethylenetriamine, have been found to display pH-tunable rheological properties without the need for a co-surfactant. For this supramolecular system, the dynamically changing interplay among the constituents is responsible for the rich phase behavior including hollow nanotubules, bilayers, and vesicles. A further hypothesis is that hollow nanotubular structure is highly desirable for achieving chain entanglement geometries with reduced mesh size. The rheological properties of the suspension were measured using a rotational rheometer. An analysis using zero-shear viscosities at various temperatures as well as differential scanning calorimetry(DSC) helped shed light on thermodynamic and phase transitions taking place. The morphology of the suspension was analyzed by using a combination of small angle x-ray scattering(SAXS) and atomic force microscopy(AFM). Large steady-shear viscosities (up to ~160 Pa.s) and viscoelastic behavior was observed in acidic conditions which diminished upon increasing the pH. A novel analysis consisting of measured thermodynamic quantities such as activation energy(E a ) and enthalpy of transition(ΔH T ) further allude to the rich pH-sensitive nanoarchitecture of the system. Rather than commonly observed wormlike micelles, hollow nanotubules, as long as 1.6 µm were observed at pH 4 which disintegrated to bilayer sheets and vesicles upon increasing pH. Finally, gaining a comprehensive understanding from all the results, a transition mechanism between different suspension architectures was proposed.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
A deep learning approach for semantic segmentation of unbalanced data in electron tomography of catalytic materials
In computed TEM tomography, image segmentation represents one of the most basic tasks with implications not only for 3D volume visualization, but more importantly for quantitative 3D analysis. In case of large and complex 3D data sets, segmentation can be an extremely difficult and laborious task, and thus has been one of the biggest hurdles for comprehensive 3D analysis. Heterogeneous catalysts have complex surface and bulk structures, and often sparse distribution of catalytic particles with relatively poor intrinsic contrast, which possess a unique challenge for image segmentation, including the current state-of-the-art deep learning methods. To tackle this problem, we apply a deep learning-based approach for the multi-class semantic segmentation of a γ-Alumina/Pt catalytic material in a class imbalance situation. Specifically, we used the weighted focal loss as a loss function and attached it to the U-Net’s fully convolutional network architecture. We assessed the accuracy of our results using Dice similarity coefficient (DSC), recall, precision, and Hausdorff distance (HD) metrics on the overlap between the ground-truth and predicted segmentations. Our adopted U-Net model with the weighted focal loss function achieved an average DSC score of 0.96 ± 0.003 in the γ-Alumina support material and 0.84 ± 0.03 in the Pt NPs segmentation tasks. We report an average boundary-overlap error of less than 2 nm at the 90th percentile of HD for γ-Alumina and Pt NPs segmentations. The complex surface morphology of γ-Alumina and its relation to the Pt NPs were visualized in 3D by the deep learning-assisted automatic segmentation of a large data set of high-angle annular dark-field (HAADF) scanning transmission electron microscopy (STEM) tomography reconstructions.
36 MATERIALS SCIENCE↗
Proximity Magnetism in Mn(Bi,Sb) 2 Te 4 –(Bi,Sb) 2 Te 3 /MnTe Natural Heterostructures
Magnetic topological insulators and their heterostructures provide significant opportunities to couple band topology with a nontrivial spin configuration for enhanced spintronic device performance, as well as designing magnetoelectric systems and functionalities. We find that Mn interdiffusion from MnTe when interfaced with (Bi,Sb) 2 Te 3 stabilizes as self-organized Mn(Bi,Sb) 2 Te 4 septuple lamellae among alternating (Bi,Sb) 2 Te 3 quintuple layers, as observed using scanning transmission electron microscopy and depth-sensitive polarized neutron reflectometry. We further demonstrate a valuable combination of magnetic and topological orders in these naturally formed Mn(Bi,Sb) 2 Te 4 –(Bi,Sb) 2 Te 3 heterostructures, which are exchange-coupled with MnTe. Magnetotransport experiments and quantum magnetism simulations reveal that, above its own Néel temperature T N ∼ 20 K, Mn(Bi,Sb) 2 Te 4 mediates the exchange field leading to an anomalous Hall effect at the (Bi,Sb) 2 Te 3 /MnTe interface, with an enhanced interfacial T N exceeding 200 K, approaching that of the bulk MnTe. This magnetic interface, in turn, allows a robust and deterministic spin–orbit torque switching without an external magnetic field at a low critical current density of 3 × 10 5 A cm –2 . The antiferromagnetically coupled architecture of Mn(Bi,Sb) 2 Te 4 –(Bi,Sb) 2 Te 3 /MnTe, featuring magnetic and topological proximity effects across a chalcogenide backbone, is rich in fundamental interface physics and holds the potential for practical applications in spintronics.
magnetic topological insulator↗
Structural and Mechanical Analysis of Individual Mineralized Collagen Fibrils Using In Situ Transmission Electron Microscopy
Bone serves as an example of nature’s architectured material with its characteristic blend of strength and toughness, all at a lightweight design. Given the hierarchical nature of these materials, it is essential to understand the governing mechanisms and organization of their constituents across length scales for bioinspired structural design. Despite recent advances in transmission electron microscopy (TEM) that have allowed us to witness the hierarchical arrangement of bone at micro-down to the nanoscale, we are still missing the details about the structural organization and mechanical properties of the main building blocks of bone─mineralized collagen fibrils (MCFs). Here, we present a method to extract individual MCFs from nature’s model material, mineralized turkey leg tendon, using a dropcasting procedure. By isolating the MCFs onto TEM supporting grids, we visualized the arrangement of organic and mineral phases within individual MCFs at the nanoscale. Using a four-dimensional scanning transmission electron microscopy (4D-STEM) approach, the orientation of individual mineral crystals within the MCFs was examined. Furthermore, we conducted in situ tensile experiments, revealing exceptional tensile strains of at least 8%, demonstrating the intricate relationship between structural organization and the mechanical behavior of MCFs. These insights into the ultrastructure of mineralized tissue building blocks, as well as the proposed sample-extraction method compatible with in situ mechanical testing, provide a strong basis for research into nature-inspired material design.
4D-STEM↗
Two-layer cathode architecture for high-energy density and high-power density solid state batteries
Solid state batteries with high-energy density and high-power density require the development of thick and energy dense cathodes. Structured cathode electrodes with a double-layer configuration were enabled using a freeze tape casting technique. A bottom dense layer was utilized to enhance the energy density whereas a top porous layer with vertically aligned walls was utilized to enhance the power density. The porous structure of the power layer was achieved by ice templating this layer on top of the densified energy layer of the cathode. This configuration was found to better utilize the active material of the cathodes and was optimized using numerical simulation and computer modeling. Cells with Li metal anode and LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC622) at approximately 5 and 20 mg/cm 2 were cycled at 70 °C at different C-rates. Poly(ethylene oxide) (PEO) with lithium bis-trifluoromethanesulfonimide (LiTFSI) was used for the catholyte and the solid-state electrolyte. The structured cathodes exhibited more than double capacity values as well as better Coulombic efficiency compared to non-structured (single-layer) thick cathodes. In conclusion, synchrotron X-ray tomography and scanning electron microscopy were used to characterize the microstructure of the cathodes.
25 ENERGY STORAGE↗
Atomic-scale manipulation of buried graphene–silicon carbide interface by local electric field
Abstract Precision of scanning tunneling microscopy (STM) enables control of matter at scales of single atoms. However, transition from atomic-scale manipulation strategies to practical devices encounters fundamental problems in protection of the designer structures formed atop the surface. In this context, STM manipulation of subsurface structures on technologically relevant materials is encouraging. Here, we propose a material platform and protocols for precise manipulation of a buried graphene interface. We show that an electric field from the STM tip reversibly controls breaking and restoring of covalent bonds between the graphene buffer layer and the SiC substrate. The process involves charge redistribution at the atomically sharp interface plane under the epitaxial graphene layer(s). This buried manipulation platform is laterally defined by unit cells from the corresponding (6×6) SiC moiré lattice of the epitaxial graphene. Local and reversible electric-field-induced patterning of graphene heterostructures from the bottom interface creates an alternative architecture concept for their applications.
74 ATOMIC AND MOLECULAR PHYSICS↗