Experimental analysis of charge redistribution due to chemical bonding by high-resolution transmission electron microscopy

E+: Software for Hierarchical Modeling of Electron Scattering from Complex Structures

In modern nanobeam transmission electron microscopy methods, such as 4D-STEM, a converged electron nanobeam is scanned across a sample. Its 2D scattering pattern is recorded at each sample position, mapping the local sample structure. One of the bottlenecks in electron scattering is the analysis of the scattering data obtained from complex atomic or molecular structures. On the basis of D+ software, we developed the software E+ for analyzing electron scattering data, enabling us to model the 2D scattering pattern from any complex structure in a single orientation or a fiber. In addition, the azimuthally integrated 1D scattering curve of isotropically oriented structures (as in solutions or powders), or any other distribution of orientations, can also be computed. E+ allows the docking of geometric and/or molecular atomic models into their assembly symmetry. The assembly symmetry contains the rotations and translations of repeating subunits within a large structure. This process can be repeated hierarchically, using a bottom-up approach, adding as many subunits as needed. This procedure can be used to model the scattering data from any complex supramolecular structure at any spatial resolution, down to atomic resolution. In addition, the contribution from the solvation layers of structures in solutions can be computed in a scalable manner for large complexes. Furthermore, the Python API of E+ can be used for advanced modeling of structure factor and pair distribution functions, taking into account various effects, including thermal fluctuations, polydispersity of any structural parameters, or the intermolecular interactions between subunits. We validate E+ against the abTEM software and show a few examples, demonstrating how E+ can be used to analyze 4D-STEM electron scattering data.

Exit wave reconstruction of a focal series of images with structural changes in high-resolution transmission electron microscopy

High-resolution transmission electron microscopy (HRTEM) images can capture the atomic-resolution details of the dynamically changing structure of nanomaterials. Here, we propose a new scheme and an improved reconstruction algorithm to reconstruct the exit wave function for each image in a focal series of HRTEM images to reveal structural changes. In this scheme, the wave reconstructed from the focal series of images is treated as the initial wave in the reconstruction process for each HRTEM image. Additionally, to suppress noise at the frequencies where the signal is weak due to the modulation of the lens transfer function, a weight factor is introduced in the improved reconstruction algorithm. The advantages of the new scheme and algorithms are validated by using the HRTEM images of a natural specimen and a single-layer molybdenum disulphide. This algorithm enables image resolution enhancement and lens aberration removal, while potentially allowing the visualisation of the structural evolution of nanostructures.

Current opinion on the prospect of mapping electronic orbitals in the transmission electron microscope: State of the art, challenges and perspectives

The concept of electronic orbitals has enabled the understanding of a wide range of physical and chemical properties of solids through the definition of, for example, chemical bonding between atoms. In the transmission electron microscope, which is one of the most used and powerful analytical tools for high-spatial-resolution analysis of solids, the accessible quantity is the local distribution of electronic states. However, the interpretation of electronic state maps at atomic resolution in terms of electronic orbitals is far from obvious, not always possible, and often remains a major hurdle preventing a better understanding of the properties of the system of interest. In this review, the current state of the art of the experimental aspects for electronic state mapping and its interpretation as electronic orbitals is presented, considering approaches that rely on elastic and inelastic scattering, in real and reciprocal spaces. This work goes beyond resolving spectral variations between adjacent atomic columns, as it aims at providing deeper information about, for example, the spatial or momentum distributions of the states involved. The advantages and disadvantages of existing experimental approaches are discussed, while the challenges to overcome and future perspectives are explored in an effort to establish the current state of knowledge in this field. The aims of this review are also to foster the interest of the scientific community and to trigger a global effort to further enhance the current analytical capabilities of transmission electron microscopy for chemical bonding and electronic structure analysis.

Phytosynthesis of zinc oxide nanoparticles for enhanced antioxidant, antibacterial, and photocatalytic properties: A greener approach to environmental sustainability

Multifunctional nanoparticles (NPs) production from phytochemicals is a sustainable process and an eco-friendly method, and this technique has a variety of uses. To accomplish this, we developed zinc oxide nanoparticles (ZnONPs) using the medicinal plant Tinospora cordifolia (TC). Instruments such as UV-Vis, XRD, FTIR, FE-SEM with EDX, and high-resolution TEM were applied to characterize the biosynthesized TC-ZnONPs. According to the UV-vis spectra, the synthesized TC-ZnONPs absorb at a wavelength centered at 374 nm, which corresponds to a 3.2 eV band gap. HRTEM was used to observe the morphology of the particle surface and the actual size of the nanostructures. TC-ZnONPs mostly exhibit the shapes of rectangles and triangles with a median size of 21 nm. The XRD data of the synthesized ZnONPs exhibited a number of peaks in the 2θ range, implying their crystalline nature. TC-ZnONPs proved remarkable free radical scavenging capacity on DPPH (2,2-Diphenyl-1-picrylhydrazyl), ABTS (2,2-azino-bis-3-ethylbenzothiazoline-6-sulfonic acid), and NO (Nitric Oxide). TC-ZnONPs exhibited dynamic anti-bacterial activity through the formation of inhibition zones against Pseudomonas aeruginosa (18 ± 1.5 mm), Escherichia coli (18 ± 1.0 mm), Bacillus cereus (19 ± 0.5 mm), and Staphylococcus aureus (13 ± 1.1 mm). Additionally, when exposed to sunlight, TC-ZnONPs show excellent photocatalytic ability towards the degradation of methylene blue (MB) dye. These findings suggest that TC-ZnONPs are potential antioxidant, antibacterial, and photocatalytic agents.

Direct Quantifying Charge Transfer by 4D-STEM: A Study on Perfect and Defective Hexagonal Boron Nitride

Four-dimensional scanning transmission electron microscopy (4D-STEM) offers an attractive approach to simultaneously obtain precise structural determinations and capture details of local electric fields and charge densities. However, accurately extracting quantitative data at the atomic scale poses challenges, primarily due to probe propagation and size-related effects, which may even lead to misinterpretations of qualitative effects. In this study, we present a comprehensive analysis of electric fields and charge densities in both pristine and defective h-BN flakes. Through a combination of experiments and first-principle simulations, we demonstrate that while precise charge quantification at individual atomic sites is hindered by probe effects, 4D-STEM can directly measure charge transfer phenomena at the monolayer edge with sensitivity down to a few tenths of an electron and a spatial resolution on the order of a few angstroms.

Reliable phase quantification in focused probe electron ptychography of thin materials

Electron ptychography provides highly sensitive, dose efficient phase images which can be corrected for aberrations after the data has been acquired. This is crucial when very precise quantification is required, such as with sensitivity to charge transfer due to bonding. Drift can now be essentially eliminated as a major impediment to focused probe ptychography, which benefits from the availability of easily interpretable simultaneous Z-contrast imaging. However challenges have remained when quantifying the ptychographic phases of atomic sites. The phase response of a single atom has a negative halo which can cause atoms to reduce in phase when brought closer together. When unaccounted for, as in integrating methods of quantification, this effect can completely obscure the effects of charge transfer. Here we provide a new method of quantification that overcomes this challenge, at least for 2D materials, and is robust to experimental parameters such as noise, sample tilt.

Probing a Defect-Site-Specific Electronic Orbital in Graphene with Single-Atom Sensitivity

Visualization of individual electronic states ascribed to specific unoccupied orbitals at the atomic scale can reveal fundamental information about chemical bonding, but it is challenging since bonding often results in only subtle variations in the whole density of states. Here, we utilize atomic-resolution energy-loss near-edge fine structure (ELNES) spectroscopy to map out the electronic states attributed to specific unoccupied p_{z} orbital around a fourfold coordinated silicon point defect in graphene, which is further supported by theoretical calculations. Our results illustrate the power of atomic-resolution ELNES towards the probing of defect-site-specific electronic orbitals in monolayer crystals, providing insights into understanding the effect of chemical bonding on the local properties of defects in solids.

Imaging the electron charge density in monolayer MoS2 at the Ångstrom scale

Four-dimensional scanning transmission electron microscopy (4D-STEM) has recently gained widespread attention for its ability to image atomic electric fields with sub-Ångstrom spatial resolution. These electric field maps represent the integrated effect of the nucleus, core electrons and valence electrons, and separating their contributions is non-trivial. In this paper, we utilized simultaneously acquired 4D-STEM center of mass (CoM) images and annular dark field (ADF) images to determine the projected electron charge density in monolayer MoS2. We evaluate the contributions of both the core electrons and the valence electrons to the derived electron charge density; however, due to blurring by the probe shape, the valence electron contribution forms a nearly featureless background while most of the spatial modulation comes from the core electrons. Our findings highlight the importance of probe shape in interpreting charge densities derived from 4D-STEM and the need for smaller electron probes.

Defect Contrast with 4D-STEM: Understanding Crystalline Order with Virtual Detectors and Beam Modification

Material properties strongly depend on the nature and concentration of defects. Characterizing these features may require nano- to atomic-scale resolution to establish structure-property relationships. 4D-STEM, a technique where diffraction patterns are acquired at a grid of points on the sample, provides a versatile method for highlighting defects. Computational analysis of the diffraction patterns with virtual detectors produces images that can map material properties. Here, using multislice simulations, we explore different virtual detectors that can be applied to the diffraction patterns that go beyond the binary response functions that are possible using ordinary STEM detectors. Using graphene and lead titanate as model systems, we investigate the application of virtual detectors to study local order and in particular defects. We find that using a small convergence angle with a rotationally varying detector most efficiently highlights defect signals. With experimental graphene data, we demonstrate the effectiveness of these detectors in characterizing atomic features, including vacancies, as suggested in simulations. Phase and amplitude modification of the electron beam provides another process handle to change image contrast in a 4D-STEM experiment. We demonstrate how tailored electron beams can enhance signals from short-range order and how a vortex beam can be used to characterize local symmetry.

Electron-Beam- and Thermal-Annealing-Induced Structural Transformations in Few-Layer MnPS3

Quasi-two-dimensional (2D) manganese phosphorus trisulfide, MnPS₃, which exhibits antiferromagnetic ordering, is a particularly interesting material in the context of magnetism in a system with reduced dimensionality and its potential technological applications. Here, we present an experimental and theoretical study on modifying the properties of freestanding MnPS₃ by local structural transformations via electron irradiation in a transmission electron microscope and by thermal annealing under vacuum. In both cases we find that MnS_1-xP_x phases (0 ≤ x < 1) form in a crystal structure different from that of the host material, namely that of the α- or γ-MnS type. These phase transformations can both be locally controlled by the size of the electron beam as well as by the total applied electron dose and simultaneously imaged at the atomic scale. For the MnS structures generated in this process, our ab initio calculations indicate that their electronic and magnetic properties strongly depend on both in-plane crystallite orientation and thickness. Moreover, the electronic properties of the MnS phases can be further tuned by alloying with phosphorus. Therefore, our results show that electron beam irradiation and thermal annealing can be utilized to grow phases with distinct properties starting from freestanding quasi-2D MnPS₃.

Precise Layer Control and Electronic State Modulation of a Transition Metal Dichalcogenide via Phase-Transition-Induced Growth

Wafer-scale growth of transition metal dichalcogenides with precise control over the number of layers, and hence the electronic state is an essential technology for expanding the practical application of 2D materials. Herein, a new growth method, phase-transition-induced growth (PTG), is proposed for the precisely controlled growth of molybdenum disulfide (MoS₂ ) films consisting of one to eleven layers with spatial uniformity on a 2 in. wafer. In this method, an energetically unstable amorphous MoS_x O_y (a-MoS_x O_y ) phase is effectively converted to a thermodynamically stable crystalline MoS₂ film. The number of MoS₂ layers is readily controlled layer-by-layer by controlling the amount of Mo atoms in a-MoS_x O_y , which is also applicable for the growth of heteroatom-inserted MoS₂ . The electronic states of intrinsic and Nb-inserted MoS₂ with one and four layers grown by PTGare are analyzed based on their work functions. The work function of monolayer MoS₂ effectively increases with the substitution of Nb for Mo. As the number of layers increases to four, charge screening becomes weaker, dopant ionization becomes easier, and ultimately the work function increases further. Thus, better electronic state modulation is achieved in a thicker layer, and in this respect, PTG has the advantage of enabling precise control over the film thickness.

Identifying and manipulating single atoms with scanning transmission electron microscopy

The manipulation of individual atoms has developed from visionary speculation into an established experimental science. Using focused electron irradiation in a scanning transmission electron microscope instead of a physical tip in a scanning probe microscope confers several benefits, including thermal stability of the manipulated structures, the ability to reach into bulk crystals, and the chemical identification of single atoms. However, energetic electron irradiation also presents unique challenges, with an inevitable possibility of irradiation damage. Understanding the underlying mechanisms will undoubtedly continue to play an important role to guide experiments. Great progress has been made in several materials including graphene, carbon nanotubes, and crystalline silicon in the eight years since the discovery of electron-beam manipulation, but the important challenges that remain will determine how far we can expect to progress in the near future.

Imaging the Spatial Distribution of Electronic States in Graphene Using Electron Energy-Loss Spectroscopy: Prospect of Orbital Mapping

The spatial distributions of antibonding π^{*} and σ^{*} states in epitaxial graphene multilayers are mapped using electron energy-loss spectroscopy in a scanning transmission electron microscope. Inelastic channeling simulations validate the interpretation of the spatially resolved signals in terms of electronic orbitals, and demonstrate the crucial effect of the material thickness on the experimental capability to resolve the distribution of unoccupied states. This work illustrates the current potential of core-level electron energy-loss spectroscopy towards the direct visualization of electronic orbitals in a wide range of materials, of huge interest to better understand chemical bonding among many other properties at interfaces and defects in solids.

Making the Most of your Electrons: Challenges and Opportunities in Characterizing Hybrid Interfaces with STEM

Inspired by the unique architectures composed of hard and soft materials in natural and biological systems, synthetic hybrid structures and associated soft-hard interfaces have recently evoked significant interest. Soft matter is typically dominated by fluctuations even at room temperature, while hard matter (which often serves as the substrate or anchor for the soft component) is governed by rigid mechanical behavior. This dichotomy offers considerable opportunities to leverage the disparate properties offered by these components across a wide spectrum spanning from basic science to engineering insights with significant technological overtones. Such hybrid structures, which include polymer nanocomposites, DNA functionalized nanoparticle superlattices and metal organic frameworks to name a few, have delivered promising insights into the areas of catalysis, environmental remediation, optoelectronics, medicine, and beyond. The interfacial structure between these hard and soft phases exists across a variety of length scales and often strongly influence the functionality of hybrid systems. While scanning/transmission electron microscopy (S/TEM) has proven to be a valuable tool for acquiring intricate molecular and nanoscale details of these interfaces, the unusual nature of hybrid composites presents a suite of challenges that make assessing or establishing the classical structure-property relationships especially difficult. These include challenges associated with preparing electron-transparent samples and obtaining sufficient contrast to resolve the interface between dissimilar materials given the dose sensitivity of soft materials. We discuss each of these challenges and supplement a review of recent developments in the field with additional experimental investigations and simulations to present solutions for attaining a nano or atomic-level understanding of these interfaces. These solutions present a host of opportunities for investigating and understanding the role interfaces play in this unique class of functional materials.

Low-Temperature Nitrogen Doping of Nanocrystalline Graphene Films with Tunable Pyridinic-N and Pyrrolic-N by Cold-Wall Plasma-Assisted Chemical Vapor Deposition

We report a viable method to produce nanocrystalline graphene films on polycrystalline nickel (Ni) with enhanced N doping at low temperatures by a cold-wall plasma-assisted chemical vapor deposition (CVD) method. The growth of nanocrystalline graphene films was carried out in a benzene/ammonia/argon (C₆H₆/NH₃/Ar) system, in which the temperature of the substrate heated by Joule heating can be further lowered to 100 °C to achieve a low sheet resistance of 3.3 kΩ sq^-1 at a high optical transmittance of 97.2%. The morphological, structural, and electrical properties and the chemical compositions of the obtained N-doped nanocrystalline graphene films can be tailored by controlling the growth parameters. An increase in the concentration of atomic N from 1.42 to 11.28 atomic percent (at.%) is expected due to the synergetic effects of a high NH₃/Ar ratio and plasma power. The possible growth mechanism of nanocrystalline graphene films is also discussed to understand the basic chemical reactions that occur at such low temperatures with the presence of plasma as well as the formation of pyridinic-N- and pyrrolic-N-dominated nanocrystalline graphene. The realization of nanocrystalline graphene films with enhanced N doping at 100 °C may open great potential in developing future transparent nanodevices.

Deep Learning Segmentation of Complex Features in Atomic-Resolution Phase-Contrast Transmission Electron Microscopy Images

Phase-contrast transmission electron microscopy (TEM) is a powerful tool for imaging the local atomic structure of materials. TEM has been used heavily in studies of defect structures of two-dimensional materials such as monolayer graphene due to its high dose efficiency. However, phase-contrast imaging can produce complex nonlinear contrast, even for weakly scattering samples. It is, therefore, difficult to develop fully automated analysis routines for phase-contrast TEM studies using conventional image processing tools. For automated analysis of large sample regions of graphene, one of the key problems is segmentation between the structure of interest and unwanted structures such as surface contaminant layers. In this study, we compare the performance of a conventional Bragg filtering method with a deep learning routine based on the U-Net architecture. We show that the deep learning method is more general, simpler to apply in practice, and produces more accurate and robust results than the conventional algorithm. We provide easily adaptable source code for all results in this paper and discuss potential applications for deep learning in fully automated TEM image analysis.

Impact of quantum-chemical metrics on the machine learning prediction of electron density

Machine learning (ML) algorithms have undergone an explosive development impacting every aspect of computational chemistry. To obtain reliable predictions, one needs to maintain a proper balance between the black-box nature of ML frameworks and the physics of the target properties. One of the most appealing quantum-chemical properties for regression models is the electron density, and some of us recently proposed a transferable and scalable model based on the decomposition of the density onto an atom-centered basis set. The decomposition, as well as the training of the model, is at its core a minimization of some loss function, which can be arbitrarily chosen and may lead to results of different quality. Well-studied in the context of density fitting (DF), the impact of the metric on the performance of ML models has not been analyzed yet. In this work, we compare predictions obtained using the overlap and the Coulomb-repulsion metrics for both decomposition and training. As expected, the Coulomb metric used as both the DF and ML loss functions leads to the best results for the electrostatic potential and dipole moments. The origin of this difference lies in the fact that the model is not constrained to predict densities that integrate to the exact number of electrons N. Since an a posteriori correction for the number of electrons decreases the errors, we proposed a modification of the model, where N is included directly into the kernel function, which allowed lowering of the errors on the test and out-of-sample sets.

The abTEM code: transmission electron microscopy from first principles

Simulation of transmission electron microscopy (TEM) images or diffraction patterns is often required to interpret experimental data. Since nuclear cores dominate electron scattering, the scattering potential is typically described using the independent atom model, which completely neglects valence bonding and its effect on the transmitting electrons. As instrumentation has advanced, new measurements have revealed subtle details of the scattering potential that were previously not accessible to experiment. We have created an open-source simulation code designed to meet these demands by integrating the ability to calculate the potential via density functional theory (DFT) with a flexible modular software design. abTEM can simulate most standard imaging modes and incorporates the latest algorithmic developments. The development of new techniques requires a program that is accessible to domain experts without extensive programming experience. abTEM is written purely in Python and designed for easy modification and extension. The effective use of modern open-source libraries makes the performance of abTEM highly competitive with existing optimized codes on both CPUs and GPUs and allows us to leverage an extensive ecosystem of libraries, such as the Atomic Simulation Environment and the DFT code GPAW. abTEM is designed to work in an interactive Python notebook, creating a seamless and reproducible workflow from defining an atomic structure, calculating molecular dynamics (MD) and electrostatic potentials, to the analysis of results, all in a single, easy-to-read document.  This article provides ongoing documentation of abTEM development. In this first version, we show use cases for hexagonal boron nitride, where valence bonding can be detected, a 4D-STEM simulation of molybdenum disulfide including ptychographic phase reconstruction, a comparison of MD and frozen phonon modeling for convergent-beam electron diffraction of a 2.6-million-atom silicon system, and a performance comparison of our fast implementation of the PRISM algorithm for a decahedral 20000-atom gold nanoparticle.

The abTEM code: transmission electron microscopy from first principles

Simulation of transmission electron microscopy (TEM) images or diffraction patterns is often required to interpret experimental data. Since nuclear cores dominate electron scattering, the scattering potential is typically described using the independent atom model, which completely neglects valence bonding and its effect on the transmitting electrons. As instrumentation has advanced, new measurements have revealed subtle details of the scattering potential that were previously not accessible to experiment. We have created an open-source simulation code designed to meet these demands by integrating the ability to calculate the potential via density functional theory (DFT) with a flexible modular software design. abTEM can simulate most standard imaging modes and incorporates the latest algorithmic developments. The development of new techniques requires a program that is accessible to domain experts without extensive programming experience. abTEM is written purely in Python and designed for easy modification and extension. The effective use of modern open-source libraries makes the performance of abTEM highly competitive with existing optimized codes on both CPUs and GPUs and allows us to leverage an extensive ecosystem of libraries, such as the Atomic Simulation Environment and the DFT code GPAW. abTEM is designed to work in an interactive Python notebook, creating a seamless and reproducible workflow from defining an atomic structure, calculating molecular dynamics (MD) and electrostatic potentials, to the analysis of results, all in a single, easy-to-read document.  This article provides ongoing documentation of abTEM development. In this first version, we show use cases for hexagonal boron nitride, where valence bonding can be detected, a 4D-STEM simulation of molybdenum disulfide including ptychographic phase reconstruction, a comparison of MD and frozen phonon modeling for convergent-beam electron diffraction of a 2.6-million-atom silicon system, and a performance comparison of our fast implementation of the PRISM algorithm for a decahedral 20000-atom gold nanoparticle.

Atom-by-atom chemical identification from scanning transmission electron microscopy images in presence of noise and residual aberrations

The simple dependence of the intensity in annular dark field scanning transmission electron microscopy images on the atomic number provides (to some extent) chemical information about the sample, and even allows an elemental identification in the case of light-element single-layer samples. However, the intensity of individual atoms and atomic columns is affected by residual aberrations and the confidence of an identification is limited by the available signal to noise. Here, we show that matching a simulation to an experimental image by iterative optimization provides a reliable analysis of atomic intensities even in presence of residual non-round aberrations. We compare our new method with other established approaches demonstrating its high reliability for images recorded at limited dose and with different aberrations. This is of particular relevance for analyzing moderately beam-sensitive materials, such as most 2D materials, where the limited sample stability often makes it difficult to obtain spectroscopic information at atomic resolution.

Computer vision AC-STEM automated image analysis for 2D nanopore applications

Transmission electron microscopy (TEM) has led to important discoveries in atomic imaging and as an atom-by-atom fabrication tool. Using electron beams, atomic structures can be patterned, annealed and crystallized, and nanopores can be drilled in thin membranes. We review current progress in TEM analysis and implement a computer vision nanopore-detection algorithm that achieves a 96% pixelwise precision in TEM images of nanopores in 2D membranes (WS₂), and discuss parameter optimization including a variation on the traditional grid search and gradient ascent. Such nanopores have applications in ion detection, water filtration, and DNA sequencing, where ionic conductance through the pore should be concordant with its TEM-measured size. Standard computer vision methods have their advantages as they are intuitive and do not require extensive training data. For completeness, we briefly comment on related machine learning for 2D materials analysis and discuss relevant progress in these fields. Image analysis alongside TEM allows correlated fabrication and analysis done simultaneously in situ to engineer devices at the atomic scale.

Deep learning in electron microscopy

Deep learning is transforming most areas of science and technology, including electron microscopy. This review paper offers a practical perspective aimed at developers with limited familiarity. For context, we review popular applications of deep learning in electron microscopy. Following, we discuss hardware and software needed to get started with deep learning and interface with electron microscopes. We then review neural network components, popular architectures, and their optimization. Finally, we discuss future directions of deep learning in electron microscopy.

ab initio description of bonding for transmission electron microscopy

The simulation of transmission electron microscopy (TEM) images or diffraction patterns is often required to interpret their contrast and extract specimen features. This is especially true for high-resolution phase-contrast imaging of materials, but electron scattering simulations based on atomistic models are widely used in materials science and structural biology. Since electron scattering is dominated by the nuclear cores, the scattering potential is typically described by the widely applied independent atom model. This approximation is fast and fairly accurate, especially for scanning TEM (STEM) annular dark-field contrast, but it completely neglects valence bonding and its effect on the transmitting electrons. However, an emerging trend in electron microscopy is to use new instrumentation and methods to extract the maximum amount of information from each electron. This is evident in the increasing popularity of techniques such as 4D-STEM combined with ptychography in materials science, and cryogenic microcrystal electron diffraction in structural biology, where subtle differences in the scattering potential may be both measurable and contain additional insights. Thus, there is increasing interest in electron scattering simulations based on electrostatic potentials obtained from first principles, mainly via density functional theory, which was previously mainly required for holography. In this Review, we discuss the motivation and basis for these developments, survey the pioneering work that has been published thus far, and give our outlook for the future. We argue that a physically better justified ab initio description of the scattering potential is both useful and viable for an increasing number of systems, and we expect such simulations to steadily gain in popularity and importance.

Atomic-Scale Electrical Field Mapping of Hexagonal Boron Nitride Defects

The distribution of electric fields in hexagonal boron nitride is mapped down to the atomic level inside a scanning transmission electron microscope by using the recently introduced technique of differential phase contrast imaging. The maps are calculated and displayed in real time, along with conventional annular dark-field images, through the use of custom-developed hardware and software. An increased electric field is observed around boron monovacancies and subsequently mapped and measured relative to the perfect lattice. The edges of extended defects feature enhanced electric fields, which can be used to trap diffusing adatoms. The magnitude of the electric field produced by the different types of edges is compared to monolayer areas, confirming previous predictions regarding their stability. These observations provide insight into the properties of this interesting material, serving as a suitable platform on which to test the limits of this technique, and encourage further work, such as dynamic experiments coupled with in situ techniques.

New Insights into Co-pyrolysis among Graphitic Carbon Nitride and Organic Compounds: Carbonaceous Gas Fragments Induced Synthesis of Ultrathin Mesoporous Nitrogen-Doped Carbon Nanosheets for Heterogeneous Catalysis

N-doped carbon materials are well known as promising metal-free catalysts and applied in innumerable industrial synthetics. However, most of the N-doped carbon materials obtained by conventional synthetic means exhibit generally low mesoporosity, and their reported pore volumes reached only 1-3 cm³ g^-1, which greatly limits their further industrial application in heterogeneous catalysis. Especially for oxidation reaction of alkylbenzenes, this type of reaction is almost always accompanied by many different byproducts, while the reaction activity and selectivity are mainly affected by mesoporosity of catalysts. Traditionally, graphitic carbon nitride (GCN) is commonly considered as a self-sacrificed nitrogen source together with multifarious organic compounds to obtain N-doped carbon materials by a co-pyrolysis process. However, the mechanisms of formation process are still complex and uncontrollable to date. In this work, we present a novel co-pyrolysis synthetic strategy by a facile chemical vapor deposition method for preparing a series of ultrathin N-doped carbon nanosheets with high mesoporosity. More importantly, it is found that GCN containing abundant hydrogen bonds can be irreversibly anchored by carbonaceous gas fragments (C_xH_y⁺) released from various organic substances via thermogravimetry-differential thermal analysis coupled with mass spectrometry and X-ray photoelectron spectroscopy analysis, and the C_xH_y⁺ fragments exhibit a non-negligible role during the transformation. Our results further demonstrated that the residue of incompletely decomposed GCN is a key point to enlarge porosity in final products which are obtained via mixing pyrolysis between an organic precursor and GCN (or GCN precursors). Benefitting from the outstanding mesoporosity and ultrathin morphology, the representative ABCNS-900 exhibits excellent catalytic performance for oxidizing ethylbenzene to acetophenone with extremely low dosage and high selectivity. Our findings show a universal synthetic strategy for ultrathin N-rich carbon nanosheets with a high mesopore volume, further promoting the application of N-doped carbon materials in heterogeneous catalytic industry.

Bond Dissociation and Reactivity of HF and H2O in a Nano Test Tube

Molecular motion and bond dissociation are two of the most fundamental phenomena underpinning the properties of molecular materials. We entrapped HF and H₂O molecules within the fullerene C₆₀ cage, encapsulated within a single-walled carbon nanotube (X@C₆₀)@SWNT, where X = HF or H₂O. (X@C₆₀)@SWNT represents a class of molecular nanomaterial composed of a guest within a molecular host within a nanoscale host, enabling investigations of the interactions of isolated single di- or triatomic molecules with the electron beam. The use of the electron beam simultaneously as a stimulus of chemical reactions in molecules and as a sub-angstrom resolution imaging probe allows investigations of the molecular dynamics and reactivity in real time and at the atomic scale, which are probed directly by chromatic and spherical aberration-corrected high-resolution transmission electron microscopy imaging, or indirectly by vibrational electron energy loss spectroscopy in situ during scanning transmission electron microscopy experiments. Experimental measurements indicate that the electron beam triggers homolytic dissociation of the H-F or H-O bonds, respectively, causing the expulsion of the hydrogen atoms from the fullerene cage, leaving fluorine or oxygen behind. Because of a difference in the mechanisms of penetration through the carbon lattice available for F or O atoms, atomic fluorine inside the fullerene cage appears to be more stable than the atomic oxygen under the same conditions. The use of (X@C₆₀)@SWNT, where each molecule X is "packaged" separately from each other, in combination with the electron microscopy methods and density functional theory modeling in this work, enable bond dynamics and reactivity of individual atoms to be probed directly at the single-molecule level.

GFc7 as a Smart Growth Nanofactor for ex vivo Expansion and Cryoprotection of Humans' Hematopoietic Stem Cells

Background

Nowadays, smart synthesized nanostructures have attracted wide attention in the field of stem cell nanotechnology due to their effect on different properties of stem cells.

Methods

GFc7 growth nanofactor was synthesized based on nanochelating technology as an iron-containing copper chelator nanocomplex. The effect of this nanocomplex on the expansion and differentiation of hematopoietic stem cells (HSCs) as well as its performance as a cryoprotectant was evaluated in the present study.

Results

The results showed that the absolute count of CD34⁺ and CD34⁺CD38^- cells on days 4, 7, 10 and 13; the percentage of lactate dehydrogenase enzyme on the same days and CD34⁺CXCR4 population on day 10 were significantly increased when they were treated with GFc7 growth nanofactor in a fetal bovine serum (FBS)-free medium. This medium also led to delayed differentiation in HSCs. One noticeable result was that CD34⁺CD38^- cells cultured in an FBS medium were immediately differentiated into CD34⁺CD38⁺ cells, while CD34⁺CD38^- cells treated with GFc7 growth nanofactor in FBS medium did not show such an immediate significant differentiation. De-freezing GFc7-treated CD34⁺ cells, which were already frozen according to cord blood bank protocols, showed a higher percentage of cell viability and a larger number of colonies according to colony-forming cell assay as compared to control.

Conclusion

It can be claimed that treating HSCs with GFc7 growth nanofactor leads to quality and quantity improvement of HSCs, both in terms of expansion in vitro and freezing and de-freezing processes.

Antiphase Boundaries as Faceted Metallic Wires in 2D Transition Metal Dichalcogenides

Antiphase boundaries (APBs) in 2D transition metal dichalcogenides have attracted wide interest as 1D metallic wires embedded in a semiconducting matrix, which could be exploited in fully 2D-integrated circuits. Here, the anisotropic morphologies of APBs (i.e., linear and saw-toothed APBs) in the nanoscale are investigated. The experimental and computational results show that despite their anisotropic nanoscale morphologies, all APBs adopt a predominantly chalcogen-oriented dense structure to maintain the energetically most stable atomic configuration. Moreover, the effect of the nanoscale morphology of an APB on electron transport from two-probe field effect transistor measurements is investigated. A saw-toothed APB has a considerably lower electron mobility than a linear APB, indicating that kinks between facets are the main factors of scattering. The observations contribute to the systematical understanding of the faceted APBs and its impact on electrical transport behavior and it could potentially extend the applications of 2D materials through defect engineering to achieve the desired properties.

Quantitative Mapping of the Charge Density in a Monolayer of MoS2 at Atomic Resolution by Off-Axis Electron Holography

The electric potential, electric field, and charge density of a monolayer of MoS₂ have been quantitatively measured at atomic-scale resolution. This has been performed by off-axis electron holography using a double aberration-corrected transmission electron microscope operated at 80 kV and a low electron beam current density. Using this low dose rate and acceleration voltage, the specimen damage is limited during imaging. In order to improve the sensitivity of the measurement, a series of holograms have been acquired. Instabilities of the microscope such as the drifts of the specimen, biprism, and optical aberrations during the acquisition have been corrected by data processing. Phase images of the MoS₂ monolayer have been acquired with a sensitivity of 2π/698 rad associated with a spatial resolution of 2.4 Å. The improvement in the signal-to-noise ratio allows the charge density to be directly calculated from the phase images using Poisson's equation. Density functional theory simulations of the potential and charge density of this MoS₂ monolayer were performed for comparison to the experiment. The experimental measurements and simulations are consistent with each other, and notably, the charge density in a sulfur monovacancy (V_S) site is shown.

Boron-doped few-layer graphene nanosheet gas sensor for enhanced ammonia sensing at room temperature

Heteroatom doping in graphene is now a practiced way to alter its electronic and chemical properties to design a highly-efficient gas sensor for practical applications. In this series, here we propose boron-doped few-layer graphene for enhanced ammonia gas sensing, which could be a potential candidate for designing a sensing device. A facile approach has been used for synthesizing boron-doped few-layer graphene (BFLGr) by using a low-pressure chemical vapor deposition (LPCVD) method. Further, Raman spectroscopy has been performed to confirm the formation of graphene and XPS and FESEM characterization were carried out to validate the boron doping in the graphene lattice. To fabricate the gas sensing device, an Si/SiO₂ substrate with gold patterned electrodes was used. More remarkably, the BFLGr-based sensor exhibits an extremely quick response for ammonia gas sensing with fast recovery at ambient conditions. Hence, the obtained results for the BFLGr-based gas sensor provide a new platform to design next-generation lightweight and fast gas sensing devices.

A boron-doped few-layer LPCVD graphene sensor is successfully designed and demonstrated for enhanced NH₃ gas sensing applications.

Atomic-Precision Fabrication of Quasi-Full-Space Grain Boundaries in Two-Dimensional Hexagonal Boron Nitride

Precise control and in-depth understanding of the interfaces are crucial for the functionality-oriented material design with desired properties. Herein, via modifying the long-standing bicrystal strategy, we proposed a novel nanowelding approach to build up interfaces between two-dimensional (2D) materials with atomic precision. This method enabled us, for the first time, to experimentally achieve the quasi-full-parameter-space grain boundaries (GBs) in 2D hexagonal boron nitride (h-BN). It further helps us unravel the long-term controversy and confusion on the registry of GBs in h-BN, including (i) discriminate the relative contribution of the strain and chemical energy on the registry of GBs; (ii) identify a new dislocation core-Frank partial dislocation and four new antiphase boundaries; and (iii) confirm the universal GB faceting. Our work provides a new paradigm to the exploitation of structural-property correlation of interfaces in 2D materials.

Single-atom nickel confined nanotube superstructure as support for catalytic wet air oxidation of acetic acid

Single-atom confined materials (SACMs) have been widely researched as catalysts in many fields within recent years. However, this class of materials may not only serve as a catalyst but also as a support material for certain reactions. Here we propose a general strategy to use SACMs as supports for tuning loaded noble metal (e.g., Ru) nanoparticles with enhanced catalytic activity. As a proof of concept, a nickel single-atom confined nitrogen-doped carbon nanotube (NCNT) superstructure is prepared as a support to load noble metal Ru for catalytic wet air oxidation of acetic acid. Improved catalytic activity with a mineralization rate of ~97.5% is achieved. Further, adsorption configurations based on DFT calculations also confirm our deduction that the introduction of single-atom Ni changes the intrinsic property of NCNTs and affects the loaded active Ru nanoparticles.

Direct imaging of light-element impurities in graphene reveals triple-coordinated oxygen

Along with hydrogen, carbon, nitrogen and oxygen are the arguably most important elements for organic chemistry. Due to their rich variety of possible bonding configurations, they can form a staggering number of compounds. Here, we present a detailed analysis of nitrogen and oxygen bonding configurations in a defective carbon (graphene) lattice. Using aberration-corrected scanning transmission electron microscopy and single-atom electron energy loss spectroscopy, we directly imaged oxygen atoms in graphene oxide, as well as nitrogen atoms implanted into graphene. The collected data allows us to compare nitrogen and oxygen bonding configurations, showing clear differences between the two elements. As expected, nitrogen forms either two or three bonds with neighboring carbon atoms, with three bonds being the preferred configuration. Oxygen, by contrast, tends to bind with only two carbon atoms. Remarkably, however, triple-coordinated oxygen with three carbon neighbors is also observed, a configuration that is exceedingly rare in organic compounds.

Annular dark field scanning transmission electron microscopy is able to distinguish the contrasts between light elements. Here, the authors directly image the bonding configurations of oxygen and nitrogen atoms in defective graphene, and surprisingly identify instances of unusual triple-coordinated oxygen with three carbon neighbors.

Evidence of a purely electronic two-dimensional lattice at the interface of TMD/Bi2Se3 heterostructures

When 2D materials are vertically stacked, new physics emerges from interlayer orbital interactions and charge transfer modulated by the additional periodicity of interlayer atomic registry (moiré superlattice). Surprisingly, relatively little is known regarding the real-space distribution of the transferred charges within this framework. Here we provide the first experimental indications of a real-space, non-atomic lattice formed by interlayer coupling induced charge redistribution in vertically stacked Bi2Se3/transition metal dichalcogenide (TMD) 2D heterostructures. Robust enough to scatter 200 keV electron beams, this non-atomic lattice generates selected area diffraction patterns that correspond excellently with simulated patterns from moiré superlattices of the parent crystals suggesting their location at sites of high interlayer atomic registry. Density functional theory (DFT) predicts concentrated charge pools reside in the interlayer region, located at sites of high nearest-neighbor atomic registry, suggesting the non-atomic lattices are standalone, reside in the interlayer region, and are purely electronic.

Dedicated preparation for in situ transmission electron microscope tensile testing of exfoliated graphene

Graphene, which is one of the most promising materials for its state-of-the-art applications, has received extensive attention because of its superior mechanical properties. However, there is little experimental evidence related to the mechanical properties of graphene at the atomic level because of the challenges associated with transferring atomically-thin two-dimensional (2D) materials onto microelectromechanical systems (MEMS) devices. In this study, we show successful dry transfer with a gel material of a stable, clean, and free-standing exfoliated graphene film onto a push-to-pull (PTP) device, which is a MEMS device used for uniaxial tensile testing in in situ transmission electron microscopy (TEM). Through the results of optical microscopy, Raman spectroscopy, and TEM, we demonstrate high quality exfoliated graphene on the PTP device. Finally, the stress-strain results corresponding to propagating cracks in folded graphene were simultaneously obtained during the tensile tests in TEM. The zigzag and armchair edges of graphene confirmed that the fracture occurred in association with the hexagonal lattice structure of graphene while the tensile testing. In the wake of the results, we envision the dedicated preparation and in situ TEM tensile experiments advance the understanding of the relationship between the mechanical properties and structural characteristics of 2D materials.

Atomic electrostatic maps of 1D channels in 2D semiconductors using 4D scanning transmission electron microscopy

Defects in materials give rise to fluctuations in electrostatic fields that reflect the local charge density, but imaging this with single atom sensitivity is challenging. However, if possible, this provides information about the energetics of adatom binding, localized conduction channels, molecular functionality and their relationship to individual bonds. Here, ultrastable electron-optics are combined with a high-speed 2D electron detector to map electrostatic fields around individual atoms in 2D monolayers using 4D scanning transmission electron microscopy. Simultaneous imaging of the electric field, phase, annular dark field and the total charge in 2D MoS₂ and WS₂ is demonstrated for pristine areas and regions with 1D wires. The in-gap states in sulphur line vacancies cause 1D electron-rich channels that are mapped experimentally and confirmed using density functional theory calculations. We show how electrostatic fields are sensitive in defective areas to changes of atomic bonding and structural determination beyond conventional imaging.

Imaging electrostatic field around individual atoms or defective areas in monolayer 2D materials is crucial to understand their structural coordination. Here, the authors report local changes in specific atomic bonds and provide in-depth structural information of complex defective monolayer MoS₂ and WS₂ systems by 4D STEM.

Active Sites and Mechanism of Oxygen Reduction Reaction Electrocatalysis on Nitrogen-Doped Carbon Materials

The oxygen reduction reaction (ORR) is a core reaction for electrochemical energy technologies such as fuel cells and metal-air batteries. ORR catalysts have been limited to platinum, which meets the requirements of high activity and durability. Over the last few decades, a variety of materials have been tested as non-Pt catalysts, from metal-organic complex molecules to metal-free catalysts. In particular, nitrogen-doped graphitic carbon materials, including N-doped graphene and N-doped carbon nanotubes, have been extensively studied. However, due to the lack of understanding of the reaction mechanism and conflicting knowledge of the catalytic active sites, carbon-based catalysts are still under the development stage of achieving a performance similar to Pt-based catalysts. In addition to the catalytic viewpoint, designing mass transport pathways is required for O₂ . Recently, the importance of pyridinic N for the creation of active sites for ORR and the requirement of hydrophobicity near the active sites have been reported. Based on the increased knowledge in controlling ORR performances, bottom-up preparation of N-doped carbon catalysts, using N-containing conjugative molecules as the assemblies of the catalysts, is promising. Here, the recent understanding of the active sites and the mechanism of ORRs on N-doped carbon catalysts are reviewed.

Transferable Machine-Learning Model of the Electron Density

The electronic charge density plays a central role in determining the behavior of matter at the atomic scale, but its computational evaluation requires demanding electronic-structure calculations. We introduce an atom-centered, symmetry-adapted framework to machine-learn the valence charge density based on a small number of reference calculations. The model is highly transferable, meaning it can be trained on electronic-structure data of small molecules and used to predict the charge density of larger compounds with low, linear-scaling cost. Applications are shown for various hydrocarbon molecules of increasing complexity and flexibility, and demonstrate the accuracy of the model when predicting the density on octane and octatetraene after training exclusively on butane and butadiene. This transferable, data-driven model can be used to interpret experiments, accelerate electronic structure calculations, and compute electrostatic interactions in molecules and condensed-phase systems.

Probing the Internal Atomic Charge Density Distributions in Real Space

Probing the charge density distributions in materials at atomic scale remains an extremely demanding task, particularly in real space. However, recent advances in differential phase contrast-scanning transmission electron microscopy (DPC-STEM) bring this possibility closer by directly visualizing the atomic electric field. DPC-STEM at atomic resolutions measures how a sub-angstrom electron probe passing through a material is affected by the atomic electric field, the field between the nucleus and the surrounding electrons. Here, we perform a fully quantitative analysis which allows us to probe the charge density distributions inside atoms, including both the positive nuclear and the screening electronic charges, with subatomic resolution and in real space. By combining state-of-the-art DPC-STEM experiments with advanced electron scattering simulations we are able to map the spatial distribution of the electron cloud within individual atomic columns. This work constitutes a crucial step toward the direct atomic scale determination of the local charge redistributions and modulations taking place in materials systems.

Bridging the Gap between Reality and Ideal in Chemical Vapor Deposition Growth of Graphene

Graphene, in its ideal form, is a two-dimensional (2D) material consisting of a single layer of carbon atoms arranged in a hexagonal lattice. The richness in morphological, physical, mechanical, and optical properties of ideal graphene has stimulated enormous scientific and industrial interest, since its first exfoliation in 2004. In turn, the production of graphene in a reliable, controllable, and scalable manner has become significantly important to bring us closer to practical applications of graphene. To this end, chemical vapor deposition (CVD) offers tantalizing opportunities for the synthesis of large-area, uniform, and high-quality graphene films. However, quite different from the ideal 2D structure of graphene, in reality, the currently available CVD-grown graphene films are still suffering from intrinsic defective grain boundaries, surface contaminations, and wrinkles, together with low growth rate and the requirement of inevitable transfer. Clearly, a gap still exits between the reality of CVD-derived graphene, especially in industrial production, and ideal graphene with outstanding properties. This Review will emphasize the recent advances and strategies in CVD production of graphene for settling these issues to bridge the giant gap. We begin with brief background information about the synthesis of nanoscale carbon allotropes, followed by the discussion of fundamental growth mechanism and kinetics of CVD growth of graphene. We then discuss the strategies for perfecting the quality of CVD-derived graphene with regard to domain size, cleanness, flatness, growth rate, scalability, and direct growth of graphene on functional substrate. Finally, a perspective on future development in the research relevant to scalable growth of high-quality graphene is presented.

Single-Crystalline Nanobelts Composed of Transition Metal Ditellurides

Following the celebrated discovery of graphene, considerable attention has been directed toward the rich spectrum of properties offered by van der Waals crystals. However, studies have been largely limited to their 2D properties due to lack of 1D structures. Here, the growth of high-yield, single-crystalline 1D nanobelts composed of transition metal ditellurides at low temperatures (T ≤ 500 °C) and in short reaction times (t ≤ 10 min) via the use of tellurium-rich eutectic metal alloys is reported. The synthesized semimetallic 1D products are highly pure, stoichiometric, structurally uniform, and free of defects, resulting in high electrical performances. Furthermore, complete compositional tuning of the ternary ditelluride nanobelts is achieved with suppressed phase separation, applicable to the creation of unprecedented low-dimensional materials/devices. This approach may inspire new growth/fabrication strategies of 1D layered nanostructures, which may offer unique properties that are not available in other materials.

Materials-by-Design: Computation, Synthesis, and Characterization from Atoms to Structures

In the 50 years that succeeded Richard Feynman's exposition of the idea that there is "plenty of room at the bottom" for manipulating individual atoms for the synthesis and manufacturing processing of materials, the materials-by-design paradigm is being developed gradually through synergistic integration of experimental material synthesis and characterization with predictive computational modeling and optimization. This paper reviews how this paradigm creates the possibility to develop materials according to specific, rational designs from the molecular to the macroscopic scale. We discuss promising techniques in experimental small-scale material synthesis and large-scale fabrication methods to manipulate atomistic or macroscale structures, which can be designed by computational modeling. These include recombinant protein technology to produce peptides and proteins with tailored sequences encoded by recombinant DNA, self-assembly processes induced by conformational transition of proteins, additive manufacturing for designing complex structures, and qualitative and quantitative characterization of materials at different length scales. We describe important material characterization techniques using numerous methods of spectroscopy and microscopy. We detail numerous multi-scale computational modeling techniques that complements these experimental techniques: DFT at the atomistic scale; fully atomistic and coarse-grain molecular dynamics at the molecular to mesoscale; continuum modeling at the macroscale. Additionally, we present case studies that utilize experimental and computational approaches in an integrated manner to broaden our understanding of the properties of two-dimensional materials and materials based on silk and silk-elastin-like proteins.

Local Plasmon Engineering in Doped Graphene

Single-atom B or N substitutional doping in single-layer suspended graphene, realized by low-energy ion implantation, is shown to induce a dampening or enhancement of the characteristic interband π plasmon of graphene through a high-resolution electron energy loss spectroscopy study using scanning transmission electron microscopy. A relative 16% decrease or 20% increase in the π plasmon quality factor is attributed to the presence of a single substitutional B or N atom dopant, respectively. This modification is in both cases shown to be relatively localized, with data suggesting the plasmonic response tailoring can no longer be detected within experimental uncertainties beyond a distance of approximately 1 nm from the dopant. Ab initio calculations confirm the trends observed experimentally. Our results directly confirm the possibility of tailoring the plasmonic properties of graphene in the ultraviolet waveband at the atomic scale, a crucial step in the quest for utilizing graphene's properties toward the development of plasmonic and optoelectronic devices operating at ultraviolet frequencies.

Atomic-resolution transmission electron microscopy of electron beam–sensitive crystalline materials

High-resolution imaging of electron beam–sensitive materials is one of the most difficult applications of transmission electron microscopy (TEM). The challenges are manifold, including the acquisition of images with extremely low beam doses, the time-constrained search for crystal zone axes, the precise image alignment, and the accurate determination of the defocus value. We develop a suite of methods to fulfill these requirements and acquire atomic-resolution TEM images of several metal organic frameworks that are generally recognized as highly sensitive to electron beams. The high image resolution allows us to identify individual metal atomic columns, various types of surface termination, and benzene rings in the organic linkers. We also apply our methods to other electron beam–sensitive materials, including the organic-inorganic hybrid perovskite CH3NH3PbBr3.

Toxicity studies of nanofabricated palladium against filariasis and malaria vectors

The present study was carried out to establish the biofabrication of palladium nanoparticles (PdNPs) using the plant leaf extract of Tinospora cordifolia Miers and its toxicity studies on the larvae of filariasis vector, Culex quinquefasciatus Say and malaria vector, Anopheles subpictus Grassi. The biofabricated PdNPs were characterized by using UV-visible spectrum, FTIR, XRD, FESEM, EDX and HRTEM. HRTEM confirmed the PdNPs were slightly agglomerated and spherical in shape and the average size was 16 nm. Gas chromatography and mass spectrometry analysis result revealed that the major constituent present in the T. cordifolia leaf extract is 2,4-di-tert-butylphenol (31.79%) whereas the minor compounds are 1-hexadecanol (7.97%), 1-octadecanol (7.70%), 1-eicosanol (6.85%), behenic alcohol (5.36%), 1-tetradecene (6.22%), cyclotetradecane (6.23%), 1-hexadecene (7.97%), 1-octadecene (7.70%), 1-eicosene (6.85%), and 1-docosene (5.36%). T. cordifolia leaf extract exhibited the larvicidal activity against the fourth instar larvae of C. quinquefasciatus and A. subpictus with the values of LC₅₀ = 59.857 and 54.536 mg/L; LC₉₀ = 113.445 and 108.940 mg/L, respectively. The highest toxicity was observed in the biofabricated PdNPs against the fourth instar larvae of C. quinquefasciatus and A. subpictus with the values of LC₅₀ = 6.090 and 6.454 mg/L; LC₉₀ = 13.689 and 13.849 mg/L, respectively. Concerning non-target effects, Poecilia reticulata were exposed to PdNPs for 24 h and did not exhibit any noticeable toxicity. Overall, our findings strongly suggest that PdNPs is a perfect ecological and inexpensive approach for the control of filariasis and malaria vectors.

N-Doped Graphene with Low Intrinsic Defect Densities via a Solid Source Doping Technique

N-doped graphene with low intrinsic defect densities was obtained by combining a solid source doping technique and chemical vapor deposition (CVD). The solid source for N-doping was embedded into the copper substrate by NH₃ plasma immersion. During the treatment, NH₃ plasma radicals not only flattened the Cu substrate such that the root-mean-square roughness value gradually decreased from 51.9 nm to 15.5 nm but also enhanced the nitrogen content in the Cu substrate. The smooth surface of copper enables good control of graphene growth and the decoupling of height fluctuations and ripple effects, which compensate for the Coulomb scattering by nitrogen incorporation. On the other hand, the nitrogen atoms on the pre-treated Cu surface enable nitrogen incorporation with low defect densities, causing less damage to the graphene structure during the process. Most incorporated nitrogen atoms are found in the pyrrolic configuration, with the nitrogen fraction ranging from 1.64% to 3.05%, while the samples exhibit low defect densities, as revealed by Raman spectroscopy. In the top-gated graphene transistor measurement, N-doped graphene exhibits n-type behavior, and the obtained carrier mobilities are greater than 1100 cm²·V^-1·s^-1. In this study, an efficient and minimally damaging n-doping approach was proposed for graphene nanoelectronic applications.