Strain Effects on the Thermal Conductivity of 2D Materials using the Optothermal Raman Technique
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In one inventive concept, an ink includes a precursor of a graphene analogue, a thickener, and a solvent. In another inventive concept, an ink includes a graphene analogue, a thickener, and a solvent. In yet another inventive concept, an aerogel includes a three-dimensional printed structure having printed features comprised of two dimensional sheets of a graphene analogue.
2D material-based devices have received great deal of attention as they can be easily stacked to obtain multifunctionality. With their ultrathin thicknesses, such multifunctioning devices become so flexible and conformal that they can be placed onto any 3D featured surfaces. However, 2D heterostructures are typically demonstrated as stacked flakes where single or few devices can be fabricated due to lack of strategies for layer-by-layer stacking of 2D materials at the wafer scale. In this talk, I will discuss about our unique strategy to isolate wafer-scale 2D materials into monolayers and stack them into a heterostructures by using a layer-resolved splitting (LRS) technique. This technique enables my group at MIT to explore unprecedented wafer-scale 2D heterodevices including integrated photonics, 3D neuromorphic computing, and microLEDs, which will be introduced in my talk. While 2D heterostructures promise interesting futuristic devices, the performance of 2D material-based devices is substantially inferior to that of conventional 3D semiconductor materials. However, 3D materials exist as their bulk form, thus it is challenging to stack them together for heterostructures. Obviously, conformal coating of such single-crystalline bulks on 3D features is impossible. My group at MIT has recently invented a 2D materials-based layer transfer (2DLT) technique that can produce single-crystalline freestanding membranes from any compound materials with their excellent semiconducting performance. This technique is based on remote epitaxy of single-crystalline films on graphene followed by peeling from graphene. Stacking of freestanding 3D material membranes will enable unprecedented 3D heterostructures whose performance is expected to be superior to that of 2D heterostructures. I will talk about our group’s effort to apply single-crystalline freestanding membranes for flexible, conformal electronics as well as for 3D heterostructures. Finally, I will conclude my talk by discussing perspectives of coupling 2D-3D freestanding membranes for 2D-3D mixed heterostructured devices that can be enabled by our LRS and 2DLT techniques.
Abstract The advent of high-resolution electron and scanning probe microscopy imaging has opened the floodgates for acquiring atomically resolved images of bulk materials, 2D materials, and surfaces. This plethora of data contains an immense volume of information on materials structures, structural distortions, and physical functionalities. Harnessing this knowledge regarding local physical phenomena necessitates the development of the mathematical frameworks for extraction of relevant information. However, the analysis of atomically resolved images is often based on the adaptation of concepts from macroscopic physics, notably translational and point group symmetries and symmetry lowering phenomena. Here, we explore the bottom-up definition of structural units and symmetry in atomically resolved data using a Bayesian framework. We demonstrate the need for a Bayesian definition of symmetry using a simple toy model and demonstrate how this definition can be extended to the experimental data using deep learning networks in a Bayesian setting, namely rotationally invariant variational autoencoders.
Abstract Women have made significant contributions to applied physics research and development, and their participation is vital to continued progress. Recognizing these contributions is important for encouraging increased involvement and creating an equitable environment in which women can thrive. This Roadmap on Women in Applied Physics, written by women scientists and engineers, is intended to celebrate women’s accomplishments, highlight established and early career researchers enlarging the boundaries in their respective fields, and promote increased visibility for the impact women have on applied physics research. Perspectives cover the topics of plasma materials processing and propulsion, super-resolution microscopy, bioelectronics, spintronics, superconducting quantum interference device technology, quantum materials, 2D materials, catalysis and surface science, fuel cells, batteries, photovoltaics, neuromorphic computing and devices, nanophotonics and nanophononics, and nanomagnetism. Our intent is to inspire more women to enter these fields and encourage an atmosphere of inclusion within the scientific community.
Two-dimensional (2D) materials hold great promise for applications in optoelectronics, quantum information science, and energy conversion due to their remarkable properties imbued by their physical characteristics. Although heterogeneities in their intrinsic structure are the major challenges limiting their synthesis and predictable properties, they also provide a pathway to controllably tune the properties and broaden the potential of 2D materials. Heterogeneities that can be tailored, including defects, dopants, strain, edges, and layer stackings offer transformative opportunities in heterogeneous 2D materials through the introduction of novel properties for technological applications. This article provides a review of recent progress in studying heterogeneities in 2D materials. The review uses examples from our work to develop a strategy to understand the heterogeneities across multiple length scales to link the effect of heterogeneity at the nanoscale with the macroscale properties of 2D materials. We describe specific types of heterogeneities and explore novel synthesis and processing methods for their controlled production with example of the potential impact and applications enabled by their intriguing properties. Finally, we provide a perspective on how to extend the range of tunable properties through further engineering the heterogeneities in 2D materials.
The mechanical behavior of two-dimensional (2D) materials across 2D phase changes is unknown, and the finite temperature (T) elasticity of paradigmatic SnSe monolayers—ferroelectric 2D materials turning paraelectric as their unit cell turns from a rectangle into a square—is described here in a progressive manner. To begin with, their zero–T total energy landscape gives way to (Boltzmann-like) averages from which the elastic behavior is determined. Furthermore, these estimates are complemented with results from the strain-fluctuation method, which employs the energy landscape or ab initio molecular dynamics data. All approaches capture the coalescence of elastic moduli < C 11 (T) > = < C 22 (T) > due to the structural transformation. The broad evolution and sudden changes of elastic parameters < C 11 (T) >, < C 22 (T) >, and < C 12 (T) > of these atomically thin phase-change membranes establishes a heretofore overlooked connection among 2D materials and soft matter.
Two-dimensional (2D) materials have been extensively implemented as surface-enhanced Raman scattering (SERS) substrates, enabling trace-molecule detection for broad applications. However, the accurate understanding of the mechanism remains elusive because most theoretical explanations are still phenomenological or qualitative based on simplified models and rough assumptions. To advance the development of 2D material-assisted SERS, it is vital to attain a comprehensive understanding of the enhancement mechanism and a quantitative assessment of the enhancement performance. Here, the microscopic chemical mechanism of 2D material-assisted SERS is quantitatively investigated. The frequency-dependent Raman scattering cross sections suggest that the 2D materials’ SERS performance is strongly dependent on the excitation wavelengths and the molecule types. By analysis of the microscopic Raman scattering processes, the comprehensive contributions of SERS can be revealed. Beyond the widely postulated charge transfer mechanisms, the quantitative results conclusively demonstrate that the resonant transitions within 2D materials alone are also capable of enhancing the molecular Raman scattering through the diffusive scattering of phonons. Furthermore, all of these scattering routines will interfere with each other and determine the final SERS performance. Our results not only provide a complete picture of the SERS mechanisms but also demonstrate a systematic and quantitative approach to theoretically understand, predict, and promote the 2D materials SERS toward analytical applications.
In recent years, field-effect transistors (FETs) have been very promising for biosensor applications due to their high sensitivity, real-time applicability, scalability, and prospect of integrating measurement system on a chip. Non-carbon 2D materials, such as transition metal dichalcogenides (TMDCs), hexagonal boron nitride (h-BN), black phosphorus (BP), and metal oxides, are a group of new materials that have a huge potential in FET biosensor applications. In this work, we review the recent advances and remarkable studies of non-carbon 2D materials, in terms of their structures, preparations, properties and FET biosensor applications. We will also discuss the challenges facing non-carbon 2D materials-FET biosensors and their future perspectives.
Abstract Remote epitaxy has opened novel opportunities for advanced manufacturing and heterogeneous integration of two-dimensional (2D) materials and conventional (3D) materials. The lattice transparency as the fundamental principle of remote epitaxy has been studied and challenged by recent observations defying the concept. Understanding remote epitaxy requires an integrated approach of theoretical modeling and experimental validation at multi-scales because the phenomenon includes remote interactions of atoms across an atomically thin material and a few van der Waals gaps. The roles of atomically thin 2D material for the nucleation and growth of a 3D material have not been integrated into a framework of remote epitaxy research. Here, we summarize studies of remote epitaxy mechanisms with a comparison to other epitaxy techniques. In the end, we suggest the crucial topics of remote epitaxy research for basic science and applications. Graphical Abstract
The emergence of two-dimensional (2D) magnetic materials exhibiting strong magnetization at ultrathin limits above room temperature are promising for miniaturization of devices beyond Moore’s law for future energy efficient nano-electronic devices. Here, the current status, different mechanisms for the existence of magnetism, spin current injection and other magnetic properties of monolayer to few-layers of various 2D magnetic materials are reviewed. Some of the promising applications of these materials are spintronics devices such as spin valves, spin tunnel field-effect transistors, and spin filtering magnetic tunnel junctions. Due to the tunable electronic properties of these 2D materials, it's quite interesting to inject the spin current with suitable ferromagnetic contacts. For instance,black phosphorus is a layered material with a small Schottky barrier height capable of injecting spin current. This review includes many recently explored 2D magnetic materials ranging from exfoliated 2D crystals to CVD grown materials from single to several layers, demonstrating tunable layer dependent magnetic properties. We also explore some of the promising theoretical study based on 2D magnetic compounds such as 2D alkali-based chromium chalcogenides, which shows ferromagnetic as well as semiconducting behavior. The layer-dependent magnetic ordering has been observed in layered compounds like 1T-CrTe 2 , VSe 2 , CrI 3 , and Fe 3 GeTe 2 , which have great potential for the future applications in magnetic based electronic devices. Finally, we emphasize the challenges, opportunities and future directions of the 2D magnetic materials, where new discoveries might have outstanding impact in transformational scientific breakthroughs towards memory, spintronics, optoelectronics and other multifunctional device applications.
As layered materials, transition metal dichalcogenides (TMDCs) are promising two-dimensional (2D) materials. Interestingly, the characteristics of these materials are transformed from bulk to monolayer. The atomically thin TMDC materials can be a good alternative to group III–V and graphene because of their emerging tunable electrical, optical, and magnetic properties. Although 2D monolayers from natural TMDC materials exhibit the purest form, they have intrinsic defects that limit their application. However, the synthesis of TMDC materials using the existing fabrication tools and techniques is also not immune to defects. Additionally, it is difficult to synthesize wafer-scale TMDC materials for a multitude of factors influencing grain growth mechanisms. While defect engineering techniques may reduce the percentage of defects, the available methods have constraints for healing defects at the desired level. Thus, this holistic review of 2D TMDC materials encapsulates the fundamental structure of TMDC materials, including different types of defects, named zero-dimensional (0D), one-dimensional (1D), and two-dimensional (2D). Moreover, the existing defect engineering methods that relate to both formation of and reduction in defects have been discussed. Finally, an attempt has been made to correlate the impact of defects and the properties of these TMDC materials.
Two-dimensional (2D) materials that can host qubits with long spin coherence time (T 2 ) have the distinct advantage of integrating easily with existing microelectronic and photonic platforms, making them attractive for designing novel quantum devices with enhanced performance. However, the relative lack of 2D materials as spin qubit hosts, as well as appropriate substrates that can help maintain long T 2 , necessitates a strategy to search for candidates with robust spin coherence. Here, we develop a high-throughput computational workflow to predict the nuclear spin bath-driven qubit decoherence and T 2 in 2D materials and heterostructures. We initially screen 1172 2D materials and find 189 monolayers with T 2 > 1 ms, higher than that of naturally-abundant diamond. We then construct 1554 lattice-commensurate heterostructures between high-T 2 2D materials and select 3D substrates, and we find that T 2 is generally lower in a heterostructure than in the bare 2D host material; however, low-noise substrates (such as CeO 2 and CaO) can help maintain high T 2 . To further accelerate the material screening effort, we derive analytical models that enable rapid predictions of T 2 for 2D materials and heterostructures. The models offer a simple, yet quantitative, way to determine the relative contributions to decoherence from the nuclear spin baths of the 2D host and substrate in a heterostructural system. By developing a high-throughput workflow and analytical models, we expand the genome of 2D materials and their spin coherence times for the development of spin qubit platforms.
Atomic layer deposition (ALD) on mechanically exfoliated 2D layered materials spontaneously produces network patterns of metal oxide nanoparticles in triangular and linear deposits on the basal surface. The network patterns formed under a range of ALD conditions and were independent of the orientation of the substrate in the ALD reactor. The patterns were produced on MoS 2 or HOPG when either tetrakis(dimethylamido)titanium or bis(ethylcyclopentadienyl)manganese were used as precursors, suggesting that the phenomenon is general for 2D materials. Transmission electron microscopy revealed the presence, prior to deposition, of dislocation networks along the basal plane of mechanically exfoliated 2D flakes, indicating that periodical basal plane defects related to disruptions in the van der Waals stacking of layers, such as perfect line dislocations and triangular extended stacking faults networks, introduce a surface reactivity landscape that leads to the emergence of patterned deposition.
Layer transfer techniques have been extensively explored for semiconductor device fabrication as a path to reduce costs and to form heterogeneously integrated devices. These techniques entail isolating epitaxial layers from an expensive donor wafer to form freestanding membranes. However, current layer transfer processes are still low-throughput and too expensive to be commercially suitable. Here we report a high-throughput layer transfer technique that can produce multiple compound semiconductor membranes from a single wafer. We directly grow two-dimensional (2D) materials on III–N and III–V substrates using epitaxy tools, which enables a scheme comprised of multiple alternating layers of 2D materials and epilayers that can be formed by a single growth run. Each epilayer in the multistack structure is then harvested by layer-by-layer mechanical exfoliation, producing multiple freestanding membranes from a single wafer without involving time-consuming processes such as sacrificial layer etching or wafer polishing. Moreover, atomic-precision exfoliation at the 2D interface allows for the recycling of the wafers for subsequent membrane production, with the potential for greatly reducing the manufacturing cost.
For future of electronics such as bioelectronics, 3D integrated electronics, and bendable electronics, needs for flexibility and stackability of electronic products have substantially grown up. However, conventional wafer-based single-crystalline semiconductors cannot catch up with such trends because they are bound to the thick rigid wafers such that they are neither flexible nor stackable. Although polymer-based organic electronic materials are more compatible as they are mechanically complaint and less costly than inorganic counterparts, their electronic/photonic performance is substantially inferior to that of single-crystalline inorganic materials. For the past few decades, many different strategies to mitigate such performance-mechanical compliance dilemma by developing methods to obtain cheap, flexible, stackable, single-crystalline inorganic systems. In today’s talk, I will discuss about various strategies to realize such a dream electronic system and how these strategies unlock new ways of manufacturing advanced electronic systems. One of the most promising approaches is to fabricate freestanding ultrathin membranes from existing functional material wafers by peeling the active layers from the top. I will overview all freestanding membrane methods and especially dive deeply into 2D materials-based layer transfer (2DLT) technique that has been recently emerging as one of the very promising options. In the 2DLT process, one can produce single-crystalline freestanding membranes from 3D materials by performing remote epitaxy or van der Waals epitaxy on 2D materials followed by peeling active single-crystalline films from the 2D materials. I will discuss about the challenges and opportunities of this technology. In addition, I will present unprecedented artificial heterostructures that can be enabled by stacking those freestanding 3D material membranes.
Point defects such as vacancies and impurity atoms strongly impact the performance of 2D materials. Traditional efforts often rely on manual detection, a process that is time-intensive, prone to human error, and challenging to scale. Here we leverage machine learning (ML) methods to identify and quantify vacancies within 2D transition metal carbides (Ti3C2, MXenes), aiming to expedite detection while improving accuracy. MXenes exhibit valuable defect-defined electrochemical properties, but we currently lack statistical understanding of defect topology needed to fully harness these materials. We employ a convolutional neural network for semantic segmentation of experimental MXene images, opening an opportunity to conduct a rigorous statistical study on defect hierarchy while investigating local relaxation in the lattice. We show how the integration of ML can yield fundamental insight into point defects, providing a powerful tool that will play an increasingly crucial role in the future of materials science.
Point defects such as vacancies and impurity atoms strongly impact the performance of 2D materials. Traditional efforts often rely on manual detection, a process that is time-intensive, prone to human error, and challenging to scale. Here we leverage machine learning (ML) methods to identify and quantify vacancies within 2D transition metal carbides (Ti3C2, MXenes), aiming to expedite detection while improving accuracy. MXenes exhibit valuable defect-defined electrochemical properties, but we currently lack statistical understanding of defect topology needed to fully harness these materials. Here we employ a convolutional neural network for semantic segmentation of experimental MXene images, opening an opportunity to conduct a rigorous statistical study on defect hierarchy while investigating local relaxation in the lattice. We show how the integration of ML can yield fundamental insight into point defects, providing a powerful tool that will play an increasingly crucial role in the future of materials science.