The successful discovery and isolation of graphene in 2004, and the subsequent synthesis of layered semiconductors and heterostructures beyond graphene have led to the exploding field of two-dimensional (2D) materials that explore their growth, new atomic-scale physics, and potential device applications. This review aims to provide an overview of theoretical, computational, and machine learning methods and tools at multiple length and time scales, and discuss how they can be utilized to assist/guide the design and synthesis of 2D materials beyond graphene. We focus on three methods at different length and time scales as follows: (i) nanoscale atomistic simulations including density functional theory (DFT) calculations and molecular dynamics simulations employing empirical and reactive interatomic potentials; (ii) mesoscale methods such as phase-field method; and (iii) macroscale continuum approaches by coupling thermal and chemical transport equations. We discuss how machine learning can be combined with computation and experiments to understand the correlations between structures and properties of 2D materials, and to guide the discovery of new 2D materials. We will also provide an outlook for the applications of computational approaches to 2D materials synthesis and growth in general.npj Computational Materials (2020) 6:22 ; https://doi.

Transition metal dichalcogenides (TMDCs) are potential materials for future optoelectronic devices. Grain boundaries (GBs) can significantly influence the optoelectronic properties of TMDC materials. Here, we have investigated tungsten diselenide (WSe2)...

Reproducible wafer-scale growth of two-dimensional (2D) materials using the Chemical Vapor Deposition (CVD) process with precise control over their properties is challenging due to a lack of understanding of the growth mechanisms spanning over several length scales and sensitivity of the synthesis to subtle changes in growth conditions. A multiscale computational framework coupling Computational Fluid Dynamics (CFD), Phase-Field (PF), and reactive Molecular Dynamics (MD) was developed – called the CPM model – and experimentally verified. Correlation between theoretical predictions and thorough experimental measurements for a Metal-Organic CVD (MOCVD)-grown WSe2 model material revealed the full power of this computational approach. Large-area uniform 2D materials are synthesized via MOCVD, guided by computational analyses. The developed computational framework provides the foundation for guiding the synthesis of wafer-scale 2D materials with precise control over the coverage, morphology, and properties, a critical capability for fabricating electronic, optoelectronic, and quantum computing devices.

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Field deployment is critical to developing numerous sensitive impedance transducers. Precise, cost-effective, and real-time readout units are being sought to interface these sensitive impedance transducers for various clinical or environmental applications. This paper presents a general readout method with a detailed design procedure for interfacing impedance transducers that generate small fractional changes in the impedance characteristics after detection. The emphasis of the design is obtaining a target response resolution considering the accuracy in real-time. An entire readout unit with amplification/filtering and real-time data acquisition and processing using a single microcontroller is proposed. Most important design parameters, such as the signal-to-noise ratio (SNR), common-mode-to-differential conversion, digitization configuration/speed, and the data processing method are discussed here. The studied process can be used as a general guideline to design custom readout units to interface with various developed transducers in the laboratory and verify the performance for field deployment and commercialization. A single frequency readout unit with a target 8-bit resolution to interface differentially placed transducers (e.g., bridge configuration) is designed and implemented. A single MCU is programmed for real-time data acquisition and sine fitting. The 8-bit resolution is achieved even at low SNR levels of roughly 7 dB by setting the component values and fitting algorithm parameters with the given methods.