We report how the presence of electron-beam-induced sulfur vacancies affects first-order Raman modes and correlate the effects with the evolution of the in situ transmission-electron microscopy ...two-terminal conductivity of monolayer MoS2 under electron irradiation. We observe a red-shift in the E′ Raman peak and a less pronounced blue-shift in the A′1 peak with increasing electron dose. Using energy-dispersive X-ray spectroscopy and selected-area electron diffraction, we show that irradiation causes partial removal of sulfur and correlate the dependence of the Raman peak shifts with S vacancy density (a few %). This allows us to quantitatively correlate the frequency shifts with vacancy concentration, as rationalized by first-principles density functional theory calculations. In situ device current measurements show an exponential decrease in channel current upon irradiation. Our analysis demonstrates that the observed frequency shifts are intrinsic properties of the defective systems and that Raman spectroscopy can be used as a quantitative diagnostic tool to characterize MoS2-based transport channels.
The vibrational properties of twisted bilayer graphene (tBLG) show complex features, due to the intricate energy landscape of its low-symmetry configurations. A machine learning-based approach is ...developed to provide a continuous model between the twist angle and the simulated Raman spectra of tBLGs. Extracting the structural information of the twist angle from Raman spectra corresponds to solving a complicated inverse problem. Once trained, the machine learning regressors (MLRs) quickly provide predictions without human bias and with an average 98% of the data variance being explained by the model. The significant spectral features learned by MLRs are analyzed revealing the intensity profile near the calculated G-band to be the most important feature. The trained models are tested on noise-containing test data demonstrating their robustness. The transferability of the present models to experimental Raman spectra is discussed in the context of validation of the level of theory used for construction of the analyzed database. This work serves as a proof of concept that machine-learning analysis is a potentially powerful tool for interpretation of Raman spectra of tBLG and other 2D materials.
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Graphene, a honeycomb sp2 hybridized carbon lattice, is a promising building block for hybrid-nanomaterials due to its electrical, mechanical, and optical properties. Graphene can be readily obtained ...through mechanical exfoliation, solution-based deposition of reduced graphene oxide (rGO), and chemical vapor deposition (CVD). The resulting graphene films’ topology is two-dimensional (2D) surface. Recently, synthesis of three-dimensional (3D) graphitic networks supported or templated by nanoparticles, foams, and hydrogels was reported. However, the resulting graphene films lay flat on the surface, exposing 2D surface topology. Out-of-plane grown carbon nanostructures, such as vertically aligned graphene sheets (VAGS) and vertical carbon nanowalls (CNWs), are still tethered to 2D surface. 3D morphology of out-of-plane growth of graphene hybrid-nanomaterials which leverages graphene's outstanding surface-to-volume ratio has not been achieved to date. Here we demonstrate highly controlled synthesis of 3D out-of-plane single- to few-layer fuzzy graphene (3DFG) on a Si nanowire (SiNW) mesh template. By varying graphene growth conditions (CH4 partial pressure and process time), we control the size, density, and electrical properties of the NW templated 3DFG (NT-3DFG). 3DFG growth can be described by a diffusion-limited-aggregation (DLA) model. The porous NT-3DFG meshes exhibited high electrical conductivity of ca. 2350 S m−1. NT-3DFG demonstrated exceptional electrochemical functionality, with calculated specific electrochemical surface area as high as ca. 1017 m2 g−1 for a ca. 7 μm thick mesh. This flexible synthesis will inspire formation of complex hybrid-nanomaterials with tailored optical and electrical properties to be used in future applications such as sensing, and energy conversion and storage.
Electron beam irradiation by transmission electron microscopy (TEM) is a common and effective method for post-synthesis defect engineering in two-dimensional transition metal dichalcogenides (TMDs). ...Combining density functional theory (DFT) with relativistic scattering theory, we simulate the generation of such defects in monolayer group-VI TMDs, MoS
, WS
, MoSe
, and WSe
, focusing on two fundamental TEM-induced atomic displacement processes: chalcogen sputtering and chalcogen vacancy migration. Our calculations show that the activation energies of chalcogen sputtering depend primarily on the chalcogen species, and are smaller in selenides than in sulfides. Meanwhile, chalcogen vacancy migration activation energies hinge on the transition metal species, being smaller in TMDs containing Mo. Incorporating these energies into a relativistic, temperature-dependent cross section, we predict that, with appropriate TEM energies and temperatures, one can induce migrations in all four group-VI TMDs without simultaneously producing vacancies at a significant rate. This can allow for the formation of complicated defects and extended patterns, and thus, for the controlled manipulation of TMD crystals for targeted functionality, without the risk of substantial collateral damage.
Selective two-electron oxygen reduction reaction (ORR) offers a promising route for hydrogen peroxide synthesis, and defective sp2-carbon-based materials are attractive, low-cost electrocatalysts for ...this process. However, due to a wide range of possible defect structures formed during material synthesis, the identification and fabrication of precise active sites remain a challenge. Here, we report a graphene edge-based electrocatalyst for two-electron ORRnanowire-templated three-dimensional fuzzy graphene (NT-3DFG). NT-3DFG exhibits notable efficiency onset potential of 0.79 ± 0.01 V vs reversible hydrogen electrode (RHE), high selectivity (94 ± 2% H2O2), and tunable ORR activity as a function of graphene edge site density. Using spectroscopic surface characterization and density functional theory calculations, we find that NT-3DFG edge sites are readily functionalized by carbonyl (CO) and hydroxyl (C–OH) groups under alkaline ORR conditions. Our calculations indicate that multiple functionalized configurations at both armchair and zigzag edges may achieve a local coordination environment that allows selective, two-electron ORR. We derive a generalized geometric descriptor based on the local coordination environment that provides activity predictions of graphene surface sites within ∼0.1 V of computed values. We combine synthesis, spectroscopy, and simulations to improve active site characterization and accelerate carbon-based electrocatalyst discovery.
Resonant Raman spectra of armchair graphene nanoribbons (AGNRs) are computed using Density Functional Theory (DFT) and third-order perturbation theory. Results are benchmarked against available ...experimental data and compared to previously used theoretical approaches based on the Placzek approximation. Comparable agreement with experiments is found for both previously and presently used methods. In addition, a numerical analysis is carried out to provide a justification for the resonant modeling method based on the use of the frequency-dependent dielectric tensor in the Placzek approximation. This work also provides additional predictions and references for wide AGNRs that might be investigated with Raman scattering experiments in the future.
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Many computational models have been developed to predict the rates of atomic displacements in two-dimensional (2D) materials under electron beam irradiation. However, these models often drastically ...underestimate the displacement rates in 2D insulators, in which beam-induced electronic excitations can reduce the binding energies of the irradiated atoms. This bond softening leads to a qualitative disagreement between theory and experiment, in that substantial sputtering is experimentally observed at beam energies deemed far too small to drive atomic dislocation by many current models. To address these theoretical shortcomings, this paper develops a first-principles method to calculate the probability of beam-induced electronic excitations by coupling quantum electrodynamics (QED) scattering amplitudes to density functional theory (DFT) single-particle orbitals. The presented theory then explicitly considers the effect of these electronic excitations on the sputtering cross section. Applying this method to 2D hexagonal BN and MoS
2
significantly increases their calculated sputtering cross sections and correctly yields appreciable sputtering rates at beam energies previously predicted to leave the crystals intact. The proposed QED-DFT approach can be easily extended to describe a rich variety of beam-driven phenomena in any crystalline material.
Combining quantum electrodynamics with density functional theory, we model electronic excitation and sputtering by beam electrons in two-dimensional materials. Electronic excitations can drastically increase the sputtering rates in these materials.
Electron beam irradiation by transmission electron microscopy (TEM) is a common and effective method for post-synthesis defect engineering in two-dimensional transition metal dichalcogenides (TMDs). ...Combining density functional theory (DFT) with relativistic scattering theory, we simulate the generation of such defects in monolayer group-VI TMDs, MoS
2
, WS
2
, MoSe
2
, and WSe
2
, focusing on two fundamental TEM-induced atomic displacement processes: chalcogen sputtering and chalcogen vacancy migration. Our calculations show that the activation energies of chalcogen sputtering depend primarily on the chalcogen species, and are smaller in selenides than in sulfides. Meanwhile, chalcogen vacancy migration activation energies hinge on the transition metal species, being smaller in TMDs containing Mo. Incorporating these energies into a relativistic, temperature-dependent cross section, we predict that, with appropriate TEM energies and temperatures, one can induce migrations in all four group-VI TMDs without simultaneously producing vacancies at a significant rate. This can allow for the formation of complicated defects and extended patterns, and thus, for the controlled manipulation of TMD crystals for targeted functionality, without the risk of substantial collateral damage.
DFT combined with relativistic scattering theory simulates the formation of complicated defects and extended patterns in group-IV TMDs.
The vibrational modes of twisted bilayer graphene (tBLG) are computed and analyzed for a series of 692 twisting angle values in the 0, 30° range. To help explore new combinations of techniques not ...available in existing software, a new code is written specialized to meet the unique demands of this problem. Details of the implementation are discussed in depth, particularly in the context of other existing software solutions. In broad, the structures are relaxed using the conjugate gradient method, and then phonon normal modes are computed in the harmonic approximation using a new code optimized for large structures, modeling energy with the classical second-generation reactive empirical bond order potential (REBO) with a Kolmogorov/Crespi registry-dependent term. The structure can then be further optimized as necessary using a novel technique based on the computed phonon modes. With this, a database is constructed with the vibrational normal mode frequencies and non-resonant Raman spectra for all of the structures. When nonlinear machine learning models are applied to the dataset to predict twist angle from Raman spectra, they are found to be robust to noise and make successful predictions during cross-validation despite the spectra lacking many of the key features that have previously been identified as possible fingerprints of twist angle. This is promising evidence for the viability of creating a black box model mapping experimental spectra to twist angle using supervised machine learning. Additionally, by unfolding the phonon modes onto the first Brillouin zone (FBZ) of a single layer, it becomes viable to track the evolution of the phonon modes as a function of twist angle, and splitting of bands around the M and K points is observed which is attributed to phonon scattering by the network of solitons that arises during relaxation. The standalone Python script written to perform this unfolding will be suitable for other future work involving band structures on extremely large supercells.
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