Transistors based on two-dimensional materials for future integrated circuits

Das, Saptarshi; Sebastian, Amritanand; Pop, Eric; McClellan, Connor J.; Franklin, Aaron D.; Grasser, T.; Knobloch, Theresia; Illarionov, Yu. Yu.; Penumatcha, Ashish V.; Appenzeller, Joerg; Chen, Zhihong; Zhu, Wenjuan; Asselberghs, Inge; Li, Lain‐Jong; Avci, Uygar E.; Bhat, Navakanta; Anthopoulos, Thomas D.; Singh, Rajendra

doi:10.1038/s41928-021-00670-1

Cited by 397 publications

(329 citation statements)

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“…In contrast to silicon, 2D semiconductors retain sizable mobilities at atomic layer thicknesses below 1 nm, a thickness that also helps to suppress short-channel effects in FETs and thus allows for physical channel lengths below 5 nm (ref. 2 ). Furthermore, the integration of 2D materials in van der Waals heterostructures provides design options for energy-efficient transistors that can overcome the limitations of thermal charge-carrier injection.…”

Section: Mainmentioning

confidence: 99%

“…Charge trapping inside the gate oxide has been identified as the root cause of BTI 15 , 17 . At elevated gate biases and temperatures, charges are transferred between the channel and gate oxide in a phonon-mediated transition 18 , with charging time constants spanning a wide range, from picoseconds to years 2 , 19 . Border traps in the gate oxide close to the channel determine the long-term stability and reliability of silicon FETs 15 , whereas in 2D-material-based FETs, they typically limit device stability on much shorter timescales 20 .…”

Section: Mainmentioning

confidence: 99%

“…28 ) insulators. Besides the location of the defect bands, another essential property of insulator traps is their extremely broad distribution of time constants, ranging from the picoseconds regime up to years 2 , 19 . As these insulator traps lead to noise, hysteresis and drifts, it is important to thoroughly characterize both traps’ time constants and their energetic location within the defect bands.…”

Section: Fermi-level Tuning For Increasing Stability Of 2d Fetsmentioning

confidence: 99%

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Improving stability in two-dimensional transistors with amorphous gate oxides by Fermi-level tuning

et al. 2022

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Electronic devices based on two-dimensional semiconductors suffer from limited electrical stability because charge carriers originating from the semiconductors interact with defects in the surrounding insulators. In field-effect transistors, the resulting trapped charges can lead to large hysteresis and device drifts, particularly when common amorphous gate oxides (such as silicon or hafnium dioxide) are used, hindering stable circuit operation. Here, we show that device stability in graphene-based field-effect transistors with amorphous gate oxides can be improved by Fermi-level tuning. We deliberately tune the Fermi level of the channel to maximize the energy distance between the charge carriers in the channel and the defect bands in the amorphous aluminium gate oxide. Charge trapping is highly sensitive to the energetic alignment of the Fermi level of the channel with the defect band in the insulator, and thus, our approach minimizes the amount of electrically active border traps without the need to reduce the total number of traps in the insulator.

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Section: Mainmentioning

confidence: 99%

Section: Mainmentioning

confidence: 99%

Section: Fermi-level Tuning For Increasing Stability Of 2d Fetsmentioning

confidence: 99%

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Improving stability in two-dimensional transistors with amorphous gate oxides by Fermi-level tuning

et al. 2022

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“…Detailed reviews of applications based on flexible 2D materials are given in some papers that recently appeared in the literature. [228][229][230][231][232] In the following, we briefly review some of those applications where the mechanical and optical properties of the employed materials (i.e., TMDs) enable new opportunities. As a first example, TMDs have been found to be among the most promising 2D materials for skin-mountable electronics because of their high flexibility, robustness, and moderate bandgap energy (in the range of 1.1-2.5 eV), which provides unique optical and electrical property combinations that are hardly found even in the archetypal 2D material, graphene.…”

Section: Nanomechanical Resonators and Other Applicationsmentioning

confidence: 99%

Mechanical, Elastic, and Adhesive Properties of Two‐Dimensional Materials: From Straining Techniques to State‐of‐the‐Art Local Probe Measurements

Giorgio

Blundo

Pettinari

et al. 2022

Adv Materials Inter

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While static methods are often essential to make a material suited to a specific application, by permanently altering its properties, dynamic ones potentially enable their real-time modulation, paving the way for the development of reconfigurable devices.Within this context, strain engineering has historically been regarded as a "static" tuning method, which exploited the crystal deformations induced by the juxtaposition of materials with different lattice constants to manipulate the properties of semiconductor heterostructures [1] and improve the performance of electronic devices (e.g., CMOS-based logic technologies [2] ). In recent years, however, strain-engineering paradigms have begun to shift, leading to the development of new devices, capable of generating a dynamic modulation of the mechanical deformations induced in the active materials (and, thus, of their optoelectronic properties).Micro-and nano-electromechanical systems (MEMS and NEMS), for example, have long been used for sensing applications, thanks to their ability to transduce external stresses (e.g., applied pressure/weights, molecule adsorption,...) into electrical signals. In the opposite regime they are, at least in principle, 2D materials, such as graphene, hexagonal boron nitride (hBN), and transition-metal dichalcogenides (TMDs), are intrinsically flexible, can withstand very large strains (>10% lattice deformations), and their optoelectronic properties display a clear and distinctive response to an applied stress. As such, they are uniquely positioned both for the investigation of the effects of mechanical deformations on solid-state systems and for the exploitation of these effects in innovative devices. For example, 2D materials can be easily employed to transduce nanometric mechanical deformations into, e.g., clearly detectable electrical signals, thus enabling the fabrication of high-performance sensors; just as easily, however, external stresses can be used as a "knob" to dynamically control the properties of 2D materials, thereby leading to the realization of strain-tuneable, fully reconfigurable devices. Here, the main methods are reviewed to induce and characterize, at the nm level, mechanical deformations in 2D materials. After presenting the latest results concerning the mechanical, elastic, and adhesive properties of these unique systems, one of their most promising applications is briefly discussed: the realization of nano-electromechanical systems based on vibrating 2D membranes, potentially capable of operating at high frequencies (>100 MHz) and over a large dynamic range.The ORCID identification number(s) for the author(s) of this article can be found under https://doi.org/10.1002/admi.202102220.

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“…Geometric packings are well studied objects in discrete and computational geometry [67] and are fundamental in solid state physics modeling [66]. Although molecular crystals are considered to be embeddings in the 3D euclidean space, following the currently high interest in 2D materials [21], the same approach can also be employed here. That is, given a representation of a molecule by a polygon, the aim is to acquire the configuration that maximizes packing density and subsequently use this as a starting configuration in classical CSP workflows.…”

mentioning

confidence: 99%

Entropic trust region for densest crystallographic symmetry group packings

Torda¹,

Goulermas²,

Púček³

et al. 2022

Preprint

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Molecular crystal structure prediction (CSP) seeks the most stable periodic structure given a chemical composition of a molecule and pressure-temperature conditions. Modern CSP solvers use global optimization methods to search for structures with minimal free energy within a complex energy landscape induced by intermolecular potentials. A major caveat of these methods is that initial configurations are random, making thus the search susceptible to the convergence at local minima. Providing initial configurations that are densely packed with respect to the geometric representation of a molecule can significantly accelerate CSP. Motivated by these observations we define a class of periodic packings restricted to crystallographic symmetry groups (CSG) and design a search method for densest CSG packings in an information geometric framework. Since the CSG induce a toroidal topology on the configuration space, a non-euclidean trust region method is performed on a statistical manifold consisting of probability distributions defined on an n-dimensional flat unit torus by extending the multivariate von Mises distribution. By introducing an adaptive quantile reformulation of the fitness function into the optimization schedule we provide the algorithm a geometric characterization through local dual geodesic flows. Moreover, we examine the geometry of the adaptive selection quantile defined trust region and show that the algorithm performs a maximization of stochastic dependence among elements of the extended multivariate von Mises distributed random vector. We experimentally evaluate its behavior and performance on various densest packings of convex polygons in 2-dimensional CSG for which optimal solutions are known.

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Transistors based on two-dimensional materials for future integrated circuits

Cited by 397 publications

References 196 publications

Improving stability in two-dimensional transistors with amorphous gate oxides by Fermi-level tuning

Improving stability in two-dimensional transistors with amorphous gate oxides by Fermi-level tuning

Mechanical, Elastic, and Adhesive Properties of Two‐Dimensional Materials: From Straining Techniques to State‐of‐the‐Art Local Probe Measurements

Entropic trust region for densest crystallographic symmetry group packings

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