Screening 0D materials for 2D nanoelectronics applications

As nanoelectronic devices based on two-dimensional (2D) materials are moving towards maturity, optimization of the properties of the active 2D material must be accompanied by equal attention to optimizing the properties of and the interfaces to the other materials around it, such as electrodes, gate dielectrics, and the substrate. While these are usually either 2D or 3D materials, recently K. Liu et al. [Nat. Electron. 4, 906 (2021)] reported on the use of zero-dimensional (0D) material, consisting of vdW-bonded Sb$_2$O$_3$ clusters, as a highly promising insulating substrate and gate dielectric. Here, we report on computational screening study to find promising 0D materials for use in nanoelectronics applications, in conjunction with 2D materials in particular. By combining a database and literature searches, we found 16 materials belonging to 6 structural prototypes with high melting points and high band gaps, and a range of static dielectric constants. We carried out additional first-principles calculations to evaluate selected technologically relevant material properties, and confirmed that all these materials are van der Waals-bonded, thus allowing for facile separation of 0D clusters from the 3D host and also weakly perturbing the electronic properties of the 2D material after deposition.Comment: 10 pages, 3 figure

High-throughput computation of Raman spectra from first principles

Raman spectroscopy is a widely-used non-destructive material characterization method, which provides information about the vibrational modes of the material and therefore of its atomic structure and chemical composition. Interpretation of the spectra requires comparison to known references and to this end, experimental databases of spectra have been collected. Reference Raman spectra could also be simulated using atomistic first-principles methods but these are computationally demanding and thus the existing databases of computational Raman spectra are fairly small. In this work, we developed an optimized workflow to calculate the Raman spectra more efficiently compared to existing approaches. The workflow was benchmarked and validated by comparison to experiments and previous computational methods for select technologically relevant material systems. Using the workflow, we performed high-throughput calculations for a large set of materials (5099) belonging to many different material classes, and collected the results to a database. Finally, the contents of database are analyzed and the calculated spectra are shown to agree well with the experimental ones.Comment: 19 pages, 7 figure

Substitutional Si impurities in monolayer hexagonal boron nitride

We report the first observation of substitutional silicon atoms in single-layer hexagonal boron nitride (h-BN) using aberration corrected scanning transmission electron microscopy (STEM). The medium angle annular dark field (MAADF) images reveal silicon atoms exclusively filling boron vacancies. This structure is stable enough under electron beam for repeated imaging. Density functional theory (DFT) is used to study the energetics, structure and properties of the experimentally observed structure. The formation energies of all possible charge states of the different silicon substitutions (Si$_\mathrm{B}$, Si$_\mathrm{N}$ and Si$_\mathrm{{BN}}$) are calculated. The results reveal Si$_\mathrm{B}^{+1}$ as the most stable substitutional configuration. In this case, silicon atom elevates by 0.66{\AA} out of the lattice with unoccupied defect levels in the electronic band gap above the Fermi level. The formation energy shows a slightly exothermic process. Our results unequivocally show that heteroatoms can be incorporated into the h-BN lattice opening way for applications ranging from single-atom catalysis to atomically precise magnetic structures

Raman Spectra of Titanium Carbide MXene from Machine-Learning Force Field Molecular Dynamics

MXenes represent one of the largest class of 2D materials with promising applications in many fields and their properties tunable by the surface group composition. Raman spectroscopy is expected to yield rich information about the surface composition, but the interpretation of measured spectra has proven challenging. The interpretation is usually done via comparison to simulated spectra, but there are large discrepancies between the experimental and earlier simulated spectra. In this work, we develop a computational approach to simulate Raman spectra of complex materials that combines machine-learning force-field molecular dynamics and reconstruction of Raman tensors via projection to pristine system modes. The approach can account for the effects of finite temperature, mixed surfaces, and disorder. We apply our approach to simulate Raman spectra of titanium carbide MXene and show that all these effects must be included in order to properly reproduce the experimental spectra, in particular the broad features. We discuss the origin of the peaks and how they evolve with surface composition, which can then be used to interpret experimental results

Charged Point Defects in the Flatland: Accurate Formation Energy Calculations in Two-Dimensional Materials

Impurities and defects frequently govern materials properties, with the most prominent example being the doping of bulk semiconductors where a minute amount of foreign atoms can be responsible for the operation of the electronic devices. Several computational schemes based on a supercell approach have been developed to get insights into types and equilibrium concentrations of point defects, which successfully work in bulk materials. Here, we show that many of these schemes cannot directly be applied to two-dimensional (2D) systems, as formation energies of charged point defects are dominated by large spurious electrostatic interactions between defects in inhomogeneous environments. We suggest two approaches that solve this problem and give accurate formation energies of charged defects in 2D systems in the dilute limit. Our methods, which are applicable to all kinds of charged defects in any 2D system, are benchmarked for impurities in technologically important h-BN and MoS2 2D materials, and they are found to perform equally well for substitutional and adatom impurities.Peer reviewe

Strain-modulated defect engineering of two-dimensional materials

Strain- and defect-engineering are two powerful approaches to tailor the opto-electronic properties of two-dimensional (2D) materials, but the relationship between applied mechanical strain and behavior of defects in these systems remains elusive. Using first-principles calculations, we study the response to external strain of h-BN, graphene, MoSe2, and phosphorene, four archetypal 2D materials, which contain substitutional impurities. We find that the formation energy of the defect structures can either increase or decrease with bi-axial strain, tensile or compressive, depending on the atomic radius of the impurity atom, which can be larger or smaller than that of the host atom. Analysis of the strain maps indicates that this behavior is associated with the compressive or tensile local strains produced by the impurities that interfere with the external strain. We further show that the change in the defect formation energy is related to the change in elastic moduli of the 2D materials upon introduction of impurity, which can correspondingly increase or decrease. The discovered trends are consistent across all studied 2D materials and are likely to be general. Our findings open up opportunities for combined strain- and defect-engineering to tailor the opto-electronic properties of 2D materials, and specifically, the location and properties of single-photon emitters