Performance of integrated optical switches based on 2D materials and beyond

Yuhan YAO , Zhao CHENG , Jianji DONG , Xinliang ZHANG

Front. Optoelectron. ›› 2020, Vol. 13 ›› Issue (2) : 129 -138.

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Front. Optoelectron. ›› 2020, Vol. 13 ›› Issue (2) : 129 -138. DOI: 10.1007/s12200-020-1058-3
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Performance of integrated optical switches based on 2D materials and beyond

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Abstract

Applications of optical switches, such as signal routing and data-intensive computing, are critical in optical interconnects and optical computing. Integrated optical switches enabled by two-dimensional (2D) materials and beyond, such as graphene and black phosphorus, have demonstrated many advantages in terms of speed and energy consumption compared to their conventional silicon-based counterparts. Here we review the state-of-the-art of optical switches enabled by 2D materials and beyond and organize them into several tables. The performance tables and future projections show the frontiers of optical switches fabricated from 2D materials and beyond, providing researchers with an overview of this field and enabling them to identify existing challenges and predict promising research directions.

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Keywords

two-dimensional (2D) materials / integrated optics / optical switches / performance table

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Yuhan YAO, Zhao CHENG, Jianji DONG, Xinliang ZHANG. Performance of integrated optical switches based on 2D materials and beyond. Front. Optoelectron., 2020, 13(2): 129-138 DOI:10.1007/s12200-020-1058-3

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Introduction

Optical switches are increasingly considered for applications in optical computing and interconnections in order to meet the ever-growing performance demands in data centers [1,2]. With the advent of the Big Data era, Moore’s Law is approaching its physical limit. Traditional photonic integrated circuits (PICs) face crucial challenges in energy consumption, operation speed, and fabrication cost. As the basic units of large-scale PICs, integrated optical switches are of great significance for use in interconnections, the performance of which always determines the upper limit of the whole circuit. To provide switches with greater applicability to high-performance optoelectronics, it is essential to design an optical switch with a small footprint, low energy consumption, and fast response time.

Conventional integrated optical switches utilize variations in the effective refractive index of the waveguide produced, including the thermo-optic effect [37] or plasma dispersion [810]. However, conventional switches have hit a technical limit imposed by the properties of traditional bulk materials, which cannot adequately satisfy the growing needs [11]. Consequently, investigators have developed hybrid structures to improve the performance of optical switches, using active substances, such as two-dimensional (2D) materials [12,13] and polymers [14,15], that are introduced into the traditional optical devices. In recent years, 2D materials, such as graphene, black phosphorus, and transition-metal dichalcogenides, have become increasingly attractive for integrated photonic applications in light sources, modulators, and photodetectors [1621]. Their atomically thin structures reduce the dimensionality of the material, resulting in unique optical and electronic properties—including high electron mobility [2225], strong anisotropy [26,27], strong photoluminescence [28,29], tunable bandgaps [30,31], large optical nonlinearity [3236], etc.—that provide great opportunities for improving the performance of optoelectronic devices. In particular, the combination of 2D materials and complementary metal-oxide-semiconductor (CMOS)-compatible integrated photonics appears very promising. It can compensate for the intrinsic drawbacks of the waveguide itself [37], thus providing great potential for realizing high-performance optical switches. Note that all the optical switches mentioned below refer particularly to devices integrated with 2D materials and beyond.

In communication systems, the properties of switches, such as the extinction ratio, insertion loss, and footprint, must be carefully considered. We specifically focus on the operation speed and energy consumption because these two parameters are of most concern for realistic applications in large-scale PICs. Furthermore, we expect that future interconnect technologies will demand optical components on a chip that consume less energy than one femtojoule per bit [38]. In particular, we present complete tables containing representative optical switches, providing a useful information resource that summarizes the work in this area. In addition, the performance of various optical switches is summarized in terms of switching time and energy consumption. These data will be updated with further progress in this field to provide more support for investigators.

Criterion for statistics

The optical switches discussed in this article refer to time-domain switches or optical modulators rather than to spatial switches or optical routers that use N× N optical-switch fabric, which can be built up by connecting the basic switching cells into switching-fabric topologies [3947]. In addition, noteworthy results in mode-multiplexed photonic switches are not included [4851], as we focus exclusively on single-mode systems. All the data in the following tables and figures are taken from studies published before April 2020. Different physical mechanisms have been explored to trigger the optical switching process in integrated devices, which can be classified into all-optical, thermo-optical, and electro-optical switching. Energy consumption in integrated devices is always used to rank the switching performance [38]. To allow for a detailed and comprehensive analysis, we chose different units to evaluate the energy consumption for each type of mechanism. We selected energy per bit (E/bit) for all-optical and electro-optical switching and selected the minimum power per free spectral range (FSR) (mW/FSR) for thermo-optical switching.

Performance tables

Table 1 lists the representative studies of all-optical switches over the years. Most are 2D materials-based hybrid structures, although a few are polymer-based devices. The columns include the switching principle, material, device structure, energy consumption, switching time, and publication date. Table 2 lists several excellent thermo-optical switches. Here the 2D materials work as heat conductors or transparent heaters. Table 3 lists the best-performing electro-optical switches, which are the most studied and the closest to practical industrial applications, with the best power consumption of 0.7 fJ/bit [52].

The following charts track the progress and trends of the switching energy and switching time. Figure 1(a) shows the trend in energy consumption of all-optical and electro-optical switches in recent years. The overall energy consumption of all-optical switches based on 2D materials is 1–3 orders of magnitude lower than that of electro-optical switches, the performance of which fluctuates slightly around hundreds of femtojoules. Notably, the switching energy of optical switches with plasmonic-graphene hybrid waveguides can be reduced significantly, to 35 fJ/bit [55]. This suggests a new solution for energy-efficient processing, which is further discussed in the next section. Figure 1(b) depicts the tuning efficiency of thermo-optic switches over time. By incorporating monolayer graphene with a silicon photonic-crystal waveguide, a graphene microheater has the lowest reported power consumption (3.99 mW per FSR), which is attributed to the slow-light waveguide greatly enhancing the light-matter interactions.

Figure 2 presents the trend in switching time of all-optical, thermo-optical, and electro-optical switches over time. Overall, the speed of all three mechanisms has dropped by almost two orders of magnitude over the past 10 years. All-optical switching has the fastest switching time (sub-picosecond level), since it can be completely implemented in the optical domain, avoiding the conversion from external electronic signals to optical ones. Thermo-optical switches typically employ heating to change the phase of the light beam. Graphene, used as a transparent heater, has been integrated onto various silicon photonic-crystal waveguides to provide enhanced tuning efficiency, and it outperforms conventional metallic microheaters [61,69]. Unfortunately, the response times are relatively slow (hundreds of nanoseconds to tens of microseconds) because of the intrinsically slow thermal diffusivity. In contrast, the device response of electro-optical switches is limited by the electrical bandwidth rather than by the intrinsic speed of the material. Since graphene has an ultrahigh electron mobility [23], the modulation speed is consequently limited by the RC time constant of the modulator, which can be enhanced with structural optimization of the electro-optical modulators [71,74,76,78,79].

Next, we further subdivide optical switches into categories according to the different device structures. Figure 3 shows the performance of various switching devices in two dimensions (energy and time) simultaneously. For all-optical switches (Fig. 3(a)), photonic-crystal microcavities and plasmonic waveguides show obvious advantages on the energy-time-product line compared to conventional waveguides. For thermo-optic switches (Fig. 3(b)), Mach–Zehnder interferometer (MZI) type optical switches are all located on a roughly similar energy-time-product line, but the photonic-crystal waveguides and optimized microring resonators are located away from this line. For electro-optical switches (Fig. 3(c)), plasmonic waveguides show significant advantages.

What lies behind the statistics

Pros and cons of the three different mechanisms

As mentioned above, optical switches can be classified into all-optical, thermo-optical, and electro-optical switches, according to the switching mechanism. All-optical switches are the most promising candidates for use in PICs because of their energy-efficient power consumption and high-speed switching times, since they avoid electro-optical conversion. All-optical switches use the nonlinear properties of the material to control one light beam by another. The key to reducing energy consumption without affecting speed is effectively to enhance the nonlinear interaction in a limited volume. This can be achieved by using high-quality microring resonators, photonic-crystal microcavities, and metallic nanostructures. An all-optical switch with a graphene-loaded plasmonic waveguide shows superior performance, with an ultralow switching energy of 35 fJ/bit and an ultrafast switching time of 260 fs, thanks to the extremely strong light confinement in the plasmonic slot waveguide, which enhances the nonlinear absorption in graphene [55]. By using 2D materials as thermal conductors or transparent nanoheaters, thermo-optical switching can be achieved with a simple configuration having high efficiency, an easy fabrication process, and low cost. However, due to the slowness of thermal diffusion itself, the fastest switching time is only in the hundreds of nanoseconds. An electro-optic switch is one based on the electro-optic effect, that is, on the change in the refractive index of the material caused by a direct current (DC) or an alternating current (AC) electric field. This effect can be obtained either from nonlinear optical materials or from linear electro-optic materials. Electro-optic switching is widely used in high-speed optical interconnections, due to its ability to connect the electrical domain with the optical domain. However, it often requires complex structural optimization, and the insertion loss is relatively high, which are challenges that remain to be improved in the future.

Results for different device structures

Figure 3 illustrates schematically that the overall performance of a device is affected by the different waveguide structures, such as a photonic-crystal waveguide, plasmonic waveguide, microring, and MZI. The MZI-type optical switches are among the most commonly used building blocks in PICs, and they have great advantages in the fabrication process, manufacturing cost, and good scalability. However, because they are non-resonant devices, they have been criticized for their lower energy efficiency and less compactness. Additional control of the powers obtained from the two arms of the interferometer is also required to maximize the extinction ratio [83]. Conversely, the resonance effect in an optical microcavity is capable of enhancing the light sensitivity. Photonic-crystal waveguides and microring resonators can significantly increase the light-matter interaction inside the switch. Therefore, resonant cavities with large quality-to-volume (Q/V) ratios are very promising candidates for reducing the energy consumption and shrinking the footprint of a device. However, the resonance effect is usually for light of a specific frequency, which limits the operating-wavelength range, and both thermal and fabrication tolerance remain challenges for practical use [84]. Combinations of nanomaterials with integrated plasmonic nanostructures are also being explored to provide an alternative way to enhance the light-matter interactions [8589]. Metallic nanostructures that support surface plasmon polaritons show strong abilities to concentrate light within the subwavelength region, providing great potential for realizing high-performance optoelectronic devices with compact footprints [90].

Ultrafast integrated optical switches with ultralow switching energies remain an ongoing challenge

At present, the integration of 2D materials into photonic platforms is still limited. Although they are not very mature, 2D materials are far more accessible and flexible than their III-V counterparts [9194], and they may prove to be more adaptable for on-chip integration using simple, cheap, and scalable post-processing techniques. In the rich family of 2D materials, more candidates are worth exploring, and the bottleneck in utilizing them for large-scale applications may soon be overtaken by recent breakthroughs in wafer-scale, synthesis methods and manufacturing processes [9597]. In the past few years, assisted by 2D materials and beyond, several breakthroughs have been made in integrated optical switches, in terms of switching time and energy consumption. However, it is still difficult to reduce the energy consumption further to the attojoule level, which is essential for future large-scale PICs. This requires meticulous, systematic, and deep exploration of the mechanism responsible for enhancing light-matter interactions, that is, of the interaction mechanisms and methods for controlling multiphysical (optical, thermal, electric) fields within the medium. Based on the performance of emerging nanomaterials and plasmonic, nanophotonic, hybrid integration performs, ultrafast switching with energy consumption at the attojoule level may be achievable [98]. More effort must be devoted to this field to improve the performance further.

References

[1]

Cheng Q, Bahadori M, Glick M, Rumley S, Bergman K. Recent advances in optical technologies for data centers: a review. Optica, 2018, 5(11): 1354

[2]

Cheng Q, Rumley S, Bahadori M, Bergman K. Photonic switching in high performance datacenters. Optics Express, 2018, 26(12): 16022–16043

[3]

Geis M W, Spector S J, Williamson R C, Lyszczarz T M. Submicrosecond submilliwatt silicon-on-insulator thermooptic switch. IEEE Photonics Technology Letters, 2004, 16(11): 2514–2516

[4]

Dong P, Qian W, Liang H, Shafiiha R, Feng D, Li G, Cunningham J E, Krishnamoorthy A V, Asghari M. Thermally tunable silicon racetrack resonators with ultralow tuning power. Optics Express, 2010, 18(19): 20298–20304

[5]

Lee B S, Zhang M, Barbosa F A S, Miller S A, Mohanty A, St-Gelais R, Lipson M. On-chip thermo-optic tuning of suspended microresonators. Optics Express, 2017, 25(11): 12109–12120

[6]

Li X, Xu H, Xiao X, Li Z, Yu Y, Yu J. Fast and efficient silicon thermo-optic switching based on reverse breakdown of pn junction. Optics Letters, 2014, 39(4): 751–753

[7]

Zhao Y, Wang X, Gao D, Dong J, Zhang X. On-chip programmable pulse processor employing cascaded MZI-MRR structure. Frontiers of Optoelectronics, 2019, 12(2): 148–156

[8]

Xu Q, Manipatruni S, Schmidt B, Shakya J, Lipson M. 12.5 Gbit/s carrier-injection-based silicon micro-ring silicon modulators. Optics Express, 2007, 15(2): 430–436

[9]

Manipatruni S, Dokania R K, Schmidt B, Sherwood-Droz N, Poitras C B, Apsel A B, Lipson M. Wide temperature range operation of micrometer-scale silicon electro-optic modulators. Optics Letters, 2008, 33(19): 2185–2187

[10]

Timurdogan E, Sorace-Agaskar C M, Sun J, Shah Hosseini E, Biberman A, Watts M R. An ultralow power athermal silicon modulator. Nature Communications, 2014, 5(1): 4008

[11]

Ferrari A C, Bonaccorso F, Fal’ko V, Novoselov K S, Roche S, Bøggild P, Borini S, Koppens F H, Palermo V, Pugno N, Garrido J A, Sordan R, Bianco A, Ballerini L, Prato M, Lidorikis E, Kivioja J, Marinelli C, Ryhänen T, Morpurgo A, Coleman J N, Nicolosi V, Colombo L, Fert A, Garcia-Hernandez M, Bachtold A, Schneider G F, Guinea F, Dekker C, Barbone M, Sun Z, Galiotis C, Grigorenko A N, Konstantatos G, Kis A, Katsnelson M, Vandersypen L, Loiseau A, Morandi V, Neumaier D, Treossi E, Pellegrini V, Polini M, Tredicucci A, Williams G M, Hong B H, Ahn J H, Kim J M, Zirath H, van Wees B J, van der Zant H, Occhipinti L, Di Matteo A, Kinloch I A, Seyller T, Quesnel E, Feng X, Teo K, Rupesinghe N, Hakonen P, Neil S R, Tannock Q, Löfwander T, Kinaret J. Science and technology roadmap for graphene, related two-dimensional crystals, and hybrid systems. Nanoscale, 2015, 7(11): 4598–4810

[12]

Xia F, Wang H, Xiao D, Dubey M, Ramasubramaniam A. Two-dimensional material nanophotonics. Nature Photonics, 2014, 8(12): 899–907

[13]

Sun Z, Martinez A, Wang F. Optical modulators with 2D layered materials. Nature Photonics, 2016, 10(4): 227–238

[14]

Koos C, Vorreau P, Vallaitis T, Dumon P, Bogaerts W, Baets R, Esembeson B, Biaggio I, Michinobu T, Diederich F, Freude W, Leuthold J. All-optical high-speed signal processing with silicon–organic hybrid slot waveguides. Nature Photonics, 2009, 3(4): 216–219

[15]

Melikyan A, Alloatti L, Muslija A, Hillerkuss D, Schindler P C, Li J, Palmer R, Korn D, Muehlbrandt S, Van Thourhout D, Chen B, Dinu R, Sommer M, Koos C, Kohl M, Freude W, Leuthold J. High-speed plasmonic phase modulators. Nature Photonics, 2014, 8(3): 229–233

[16]

Mueller T, Xia F, Avouris P. Graphene photodetectors for high-speed optical communications. Nature Photonics, 2010, 4(5): 297–301

[17]

Youngblood N, Chen C, Koester S J, Li M. Waveguide-integrated black phosphorus photodetector with high responsivity and low dark current. Nature Photonics, 2015, 9(4): 247–252

[18]

Datta I, Chae S H, Bhatt G R, Tadayon M A, Li B, Yu Y, Park C, Park J, Cao L, Basov D N, Hone J, Lipson M. Low-loss composite photonic platform based on 2D semiconductor monolayers. Nature Photonics, 2020, 14(4): 256–262

[19]

Wu S, Buckley S, Schaibley J R, Feng L, Yan J, Mandrus D G, Hatami F, Yao W, Vučković J, Majumdar A, Xu X. Monolayer semiconductor nanocavity lasers with ultralow thresholds. Nature, 2015, 520(7545): 69–72

[20]

Ye Y, Wong Z J, Lu X, Ni X, Zhu H, Chen X, Wang Y, Zhang X. Monolayer excitonic laser. Nature Photonics, 2015, 9(11): 733–737

[21]

Yao Y, Xia X, Cheng Z, Wei K, Jiang X, Dong J, Zhang H. All-optical modulator using MXene inkjet-printed microring resonator. IEEE Journal of Selected Topics in Quantum Electronics, 2020, doi:10.1109/JSTQE.2020.2982985

[22]

Youngblood N, Li M. Integration of 2D materials on a silicon photonics platform for optoelectronics applications. Nanophotonics, 2016, 6(6): 1205–1218

[23]

Bolotin K I, Sikes K J, Jiang Z, Klima M, Fudenberg G, Hone J, Kim P, Stormer H L. Ultrahigh electron mobility in suspended graphene. Solid State Communications, 2008, 146(9–10): 351–355

[24]

Mas-Ballesté R, Gómez-Navarro C, Gómez-Herrero J, Zamora F. 2D materials: to graphene and beyond. Nanoscale, 2011, 3(1): 20–30

[25]

Kang K, Xie S, Huang L, Han Y, Huang P Y, Mak K F, Kim C J, Muller D, Park J. High-mobility three-atom-thick semiconducting films with wafer-scale homogeneity. Nature, 2015, 520(7549): 656–660

[26]

Tran V, Soklaski R, Liang Y, Yang L. Layer-controlled band gap and anisotropic excitons in few-layer black phosphorus. Physical Review B, 2014, 89(23): 235319

[27]

Qiao J, Kong X, Hu Z X, Yang F, Ji W. High-mobility transport anisotropy and linear dichroism in few-layer black phosphorus. Nature Communications, 2014, 5(1): 4475

[28]

Autere A, Jussila H, Dai Y, Wang Y, Lipsanen H, Sun Z. Nonlinear optics with 2D layered materials. Advanced Materials, 2018, 30(24): 1705963

[29]

Li Y, Zhang J, Huang D, Sun H, Fan F, Feng J, Wang Z, Ning C Z. Room-temperature continuous-wave lasing from monolayer molybdenum ditelluride integrated with a silicon nanobeam cavity. Nature Nanotechnology, 2017, 12(10): 987–992

[30]

Mak K F, Lee C, Hone J, Shan J, Heinz T F. Atomically thin MoS2: a new direct-gap semiconductor. Physical Review Letters, 2010, 105(13): 136805

[31]

Naguib M, Kurtoglu M, Presser V, Lu J, Niu J, Heon M, Hultman L, Gogotsi Y, Barsoum M W. Two-dimensional nanocrystals produced by exfoliation of Ti3 AlC2. Advanced Materials, 2011, 23(37): 4248–4253

[32]

Hendry E, Hale P J, Moger J, Savchenko A K, Mikhailov S A. Coherent nonlinear optical response of graphene. Physical Review Letters, 2010, 105(9): 097401

[33]

Zhang H, Virally S, Bao Q, Ping L K, Massar S, Godbout N, Kockaert P. Z-scan measurement of the nonlinear refractive index of graphene. Optics Letters, 2012, 37(11): 1856–1858

[34]

Jiang X, Liu S, Liang W, Luo S, He Z, Ge Y, Wang H, Cao R, Zhang F, Wen Q, Li J, Bao Q, Fan D, Zhang H. Broadband nonlinear photonics in few-layer MXene Ti3C2Tx (T= F, O, or OH). Laser & Photonics Reviews, 2018, 12(2): 1700229

[35]

Jiang B, Hao Z, Ji Y, Hou Y, Yi R, Mao D, Gan X, Zhao J. High-efficiency second-order nonlinear processes in an optical microfibre assisted by few-layer GaSe. Light, Science & Applications, 2020, 9(1): 63

[36]

Gu T, Petrone N, McMillan J F, van der Zande A, Yu M, Lo G Q, Kwong D L, Hone J, Wong C W. Regenerative oscillation and four-wave mixing in graphene optoelectronics. Nature Photonics, 2012, 6(8): 554–559

[37]

Li J, Liu C, Chen H, Guo J, Zhang M, Dai D. Hybrid silicon photonic devices with two-dimensional materials. Nanophotonics, 2020, doi:10.1515/nanoph-2020-0093

[38]

Miller D. Device requirements for optical interconnects to silicon chips. Proceedings of the IEEE, 2009, 97(7): 1166–1185

[39]

Lu L, Zhao S, Zhou L, Li D, Li Z, Wang M, Li X, Chen J. 16 × 16 non-blocking silicon optical switch based on electro-optic Mach-Zehnder interferometers. Optics Express, 2016, 24(9): 9295–9307

[40]

Jia H, Xia Y, Zhang L, Ding J, Fu X, Yang L. Four-port optical switch for fat-tree photonic network-on-chip. Journal of Lightwave Technology, 2017, 35(15): 3237–3241

[41]

Lee B G, Dupuis N. Silicon photonic switch fabrics: technology and architecture. Journal of Lightwave Technology, 2019, 37(1): 6–20

[42]

Jia H, Zhou T, Zhao Y, Xia Y, Dai J, Zhang L, Ding J, Fu X, Yang L. Six-port optical switch for cluster-mesh photonic network-on-chip. Nanophotonics, 2018, 7(5): 827–835

[43]

Zheng D, Doménech J D, Pan W, Zou X, Yan L, Pérez D. Low-loss broadband 5 × 5 non-blocking Si3N4 optical switch matrix. Optics Letters, 2019, 44(11): 2629

[44]

Li Z, Zhou L, Lu L, Zhao S, Li D, Chen J. 4 × 4 nonblocking optical switch fabric based on cascaded multimode interferometers. Photonics Research, 2016, 4(1): 21

[45]

Seok T J, Quack N, Han S, Muller R S, Wu M C. Large-scale broadband digital silicon photonic switches with vertical adiabatic couplers. Optica, 2016, 3(1): 64

[46]

Han S, Seok T J, Quack N, Yoo B W, Wu M C. Large-scale silicon photonic switches with movable directional couplers. Optica, 2015, 2(4): 370

[47]

Sun J, Timurdogan E, Yaacobi A, Hosseini E S, Watts M R. Large-scale nanophotonic phased array. Nature, 2013, 493(7431): 195–199

[48]

Yang L, Zhou T, Jia H, Yang S, Ding J, Fu X, Zhang L. General architectures for on-chip optical space and mode switching. Optica, 2018, 5(2): 180

[49]

Xiong Y, Priti R B, Liboiron-Ladouceur O. High-speed two-mode switch for mode-division multiplexing optical networks. Optica, 2017, 4(9): 1098

[50]

Jia H, Zhou T, Zhang L, Ding J, Fu X, Yang L. Optical switch compatible with wavelength division multiplexing and mode division multiplexing for photonic networks-on-chip. Optics Express, 2017, 25(17): 20698–20707

[51]

Zhou T, Jia H, Ding J, Zhang L, Fu X, Yang L. On-chip broadband silicon thermo-optic 2×2 four-mode optical switch for optical space and local mode switching. Optics Express, 2018, 26(7): 8375–8384

[52]

Koeber S, Palmer R, Lauermann M, Heni W, Elder D L, Korn D, Woessner M, Alloatti L, Koenig S, Schindler P C, Yu H, Bogaerts W, Dalton L R, Freude W, Leuthold J, Koos C. Femtojoule electro-optic modulation using a silicon–organic hybrid device. Light, Science & Applications, 2015, 4(2): e255

[53]

Nozaki K, Tanabe T, Shinya A, Matsuo S, Sato T, Taniyama H, Notomi M. Sub-femtojoule all-optical switching using a photonic-crystal nanocavity. Nature Photonics, 2010, 4(7): 477–483

[54]

Nozaki K, Shinya A, Matsuo S, Suzaki Y, Segawa T, Sato T, Kawaguchi Y, Takahashi R, Notomi M. Ultralow-power all-optical RAM based on nanocavities. Nature Photonics, 2012, 6(4): 248–252

[55]

Ono M, Hata M, Tsunekawa M, Nozaki K, Sumikura H, Chiba H, Notomi M. Ultrafast and energy-efficient all-optical switching with graphene-loaded deep-subwavelength plasmonic waveguides. Nature Photonics, 2020, 14(1): 37–43

[56]

Hu X, Jiang P, Ding C, Yang H, Gong Q. Picosecond and low-power all-optical switching based on an organic photonic-bandgap microcavity. Nature Photonics, 2008, 2(3): 185–189

[57]

Klein M, Badada B H, Binder R, Alfrey A, McKie M, Koehler M R, Mandrus D G, Taniguchi T, Watanabe K, LeRoy B J, Schaibley J R. 2D semiconductor nonlinear plasmonic modulators. Nature Communications, 2019, 10(1): 3264

[58]

Wang H, Yang N, Chang L, Zhou C, Li S, Deng M, Li Z, Liu Q, Zhang C, Li Z, Wang Y. CMOS-compatible all-optical modulator based on the saturable absorption of graphene. Photonics Research, 2020, 8(4): 468

[59]

Chen B, Wu H, Xin C, Dai D, Tong L. Flexible integration of free-standing nanowires into silicon photonics. Nature Communications, 2017, 8(1): 20

[60]

Yang S, Liu D C, Tan Z L, Liu K, Zhu Z H, Qin S Q. CMOS-compatible WS2-based all-optical modulator. ACS Photonics, 2018, 5(2): 342–346

[61]

Yan S, Zhu X, Frandsen L H, Xiao S, Mortensen N A, Dong J, Ding Y. Slow-light-enhanced energy efficiency for graphene microheaters on silicon photonic crystal waveguides. Nature Communications, 2017, 8(1): 14411

[62]

Song Q Q, Chen K X, Hu Z F. Low-power broadband thermo-optic switch with weak polarization dependence using a segmented graphene heater. Journal of Lightwave Technology, 2020, 38(6): 1358–1364

[63]

Liu Y, Wang H, Wang S, Wang Y, Wang Y, Guo Z, Xiao S, Yao Y, Song Q, Zhang H, Xu K. Highly efficient silicon photonic microheater based on black arsenic–phosphorus. Advanced Optical Materials, 2020, 8(6): 1901526

[64]

Cheng Z, Cao R, Guo J, Yao Y, Wei K, Gao S, Wang Y, Dong J, Zhang H. Phosphorene-assisted silicon photonic modulator with fast response time. Nanophotonics, 2020, doi:10.1515/nanoph-2019-0510

[65]

Yu L, Yin Y, Shi Y, Dai D, He S. Thermally tunable silicon photonic microdisk resonator with transparent graphene nanoheaters. Optica, 2016, 3(2): 159

[66]

Yu L, Dai D, He S. Graphene-based transparent flexible heat conductor for thermally tuning nanophotonic integrated devices. Applied Physics Letters, 2014, 105(25): 251104

[67]

Qiu C, Yang Y, Li C, Wang Y, Wu K, Chen J. All-optical control of light on a graphene-on-silicon nitride chip using thermo-optic effect. Scientific Reports, 2017, 7(1): 17046

[68]

Gan S, Cheng C, Zhan Y, Huang B, Gan X, Li S, Lin S, Li X, Zhao J, Chen H, Bao Q. A highly efficient thermo-optic microring modulator assisted by graphene. Nanoscale, 2015, 7(47): 20249–20255

[69]

Xu Z, Qiu C, Yang Y, Zhu Q, Jiang X, Zhang Y, Gao W, Su Y. Ultra-compact tunable silicon nanobeam cavity with an energy-efficient graphene micro-heater. Optics Express, 2017, 25(16): 19479–19486

[70]

Haffner C, Heni W, Fedoryshyn Y, Niegemann J, Melikyan A, Elder D L, Baeuerle B, Salamin Y, Josten A, Koch U, Hoessbacher C, Ducry F, Juchli L, Emboras A, Hillerkuss D, Kohl M, Dalton L R, Hafner C, Leuthold J. All-plasmonic Mach–Zehnder modulator enabling optical high-speed communication at the microscale. Nature Photonics, 2015, 9(8): 525–528

[71]

Cheng Z, Zhu X, Galili M, Frandsen L H, Hu H, Xiao S, Dong J, Ding Y, Oxenløwe L K, Zhang X. Double-layer graphene on photonic crystal waveguide electro-absorption modulator with 12 GHz bandwidth. Nanophotonics, 2019, doi:10.1515/nanoph-2019-0381

[72]

Gan X, Shiue R J, Gao Y, Mak K F, Yao X, Li L, Szep A, Walker D Jr, Hone J, Heinz T F, Englund D. High-contrast electrooptic modulation of a photonic crystal nanocavity by electrical gating of graphene. Nano Letters, 2013, 13(2): 691–696

[73]

Hu Y, Pantouvaki M, Van Campenhout J, Brems S, Asselberghs I, Huyghebaert C, Absil P, Van Thourhout D. Broadband 10 Gb/s operation of graphene electro-absorption modulator on silicon. Laser & Photonics Reviews, 2016, 10(2): 307–316

[74]

Phare C T, Daniel Lee Y H, Cardenas J, Lipson M. Graphene electro-optic modulator with 30 GHz bandwidth. Nature Photonics, 2015, 9(8): 511–514

[75]

Qiu C, Gao W, Vajtai R, Ajayan P M, Kono J, Xu Q. Efficient modulation of 1.55 mm radiation with gated graphene on a silicon microring resonator. Nano Letters, 2014, 14(12): 6811–6815

[76]

Liu M, Yin X, Zhang X. Double-layer graphene optical modulator. Nano Letters, 2012, 12(3): 1482–1485

[77]

Gao Y, Shiue R J, Gan X, Li L, Peng C, Meric I, Wang L, Szep A, Walker D Jr, Hone J, Englund D. High-speed electro-optic modulator integrated with graphene-boron nitride heterostructure and photonic crystal nanocavity. Nano Letters, 2015, 15(3): 2001–2005

[78]

Sorianello V, Midrio M, Contestabile G, Asselberghs I, Van Campenhout J, Huyghebaert C, Goykhman I, Ott A K, Ferrari A C, Romagnoli M. Graphene–silicon phase modulators with gigahertz bandwidth. Nature Photonics, 2018, 12(1): 40–44

[79]

Dalir H, Xia Y, Wang Y, Zhang X. Athermal broadband graphene optical modulator with 35 GHz speed. ACS Photonics, 2016, 3(9): 1564–1568

[80]

Alloatti L, Palmer R, Diebold S, Pahl K P, Chen B, Dinu R, Fournier M, Fedeli J M, Zwick T, Freude W, Koos C, Leuthold J. 100 GHz silicon–organic hybrid modulator. Light, Science & Applications, 2014, 3(5): e173

[81]

Liu M, Yin X, Ulin-Avila E, Geng B, Zentgraf T, Ju L, Wang F, Zhang X. A graphene-based broadband optical modulator. Nature, 2011, 474(7349): 64–67

[82]

Miller D A B. Energy consumption in optical modulators for interconnects. Optics Express, 2012, 20(S2 Suppl 2): A293–A308

[83]

Qiao L, Tang W, Chu T. 32 × 32 silicon electro-optic switch with built-in monitors and balanced-status units. Scientific Reports, 2017, 7(1): 42306

[84]

Reed G T, Mashanovich G, Gardes F Y, Thomson D J. Silicon optical modulators. Nature Photonics, 2010, 4(8): 518–526

[85]

Yan S, Zhu X, Dong J, Ding Y, Xiao S. 2D materials integrated with metallic nanostructures: fundamentals and optoelectronic applications. Nanophotonics, 2020, doi:10.1515/nanoph-2020-0074

[86]

Ding Y, Guan X, Zhu X, Hu H, Bozhevolnyi S I, Oxenløwe L K, Jin K J, Mortensen N A, Xiao S. Efficient electro-optic modulation in low-loss graphene-plasmonic slot waveguides. Nanoscale, 2017, 9(40): 15576–15581

[87]

Ma P, Salamin Y, Baeuerle B, Josten A, Heni W, Emboras A, Leuthold J. Plasmonically enhanced graphene photodetector featuring 100 Gbit/s data reception, high responsivity, and compact size. ACS Photonics, 2019, 6(1): 154–161

[88]

Ding Y, Cheng Z, Zhu X, Yvind K, Dong J, Galili M, Hu H, Mortensen N A, Xiao S, Oxenløwe L K. Ultra-compact integrated graphene plasmonic photodetector with bandwidth above 110 GHz. Nanophotonics, 2020, 9(2): 317–325

[89]

Ansell D, Radko I P, Han Z, Rodriguez F J, Bozhevolnyi S I, Grigorenko A N. Hybrid graphene plasmonic waveguide modulators. Nature Communications, 2015, 6(1): 8846

[90]

Emboras A, Hoessbacher C, Haffner C, Heni W, Koch U, Ma P, Fedoryshyn Y, Niegemann J, Hafner C, Leuthold J. Electrically controlled plasmonic switches and modulators. IEEE Journal of Selected Topics in Quantum Electronics, 2015, 21(4): 276–283

[91]

Srinivasan S A, Pantouvaki M, Gupta S, Chen H T, Verheyen P, Lepage G, Roelkens G, Saraswat K, Thourhout D V, Absil P, Campenhout J V. 56 Gb/s germanium waveguide electro-absorption modulator. Journal of Lightwave Technology, 2016, 34(2): 419–424

[92]

Chen L, Dong P, Lipson M. High performance germanium photodetectors integrated on submicron silicon waveguides by low temperature wafer bonding. Optics Express, 2008, 16(15): 11513–11518

[93]

Liu J, Camacho-Aguilera R, Bessette J T, Sun X, Wang X, Cai Y, Kimerling L C, Michel J. Ge-on-Si optoelectronics. Thin Solid Films, 2012, 520(8): 3354–3360

[94]

Wang Z, Tian B, Pantouvaki M, Guo W, Absil P, Van Campenhout J, Merckling C, Van Thourhout D. Room-temperature InP distributed feedback laser array directly grown on silicon. Nature Photonics, 2015, 9(12): 837–842

[95]

Liu Y, Huang Y, Duan X. Van der Waals integration before and beyond two-dimensional materials. Nature, 2019, 567(7748): 323–333

[96]

Bae S H, Kum H, Kong W, Kim Y, Choi C, Lee B, Lin P, Park Y, Kim J. Integration of bulk materials with two-dimensional materials for physical coupling and applications. Nature Materials, 2019, 18(6): 550–560

[97]

Stanford M G, Rack P D, Jariwala D. Emerging nanofabrication and quantum confinement techniques for 2D materials beyond graphene. npj 2D Materials and Applications, 2018, 2(1): 20

[98]

Sorger V J, Amin R, Khurgin J B, Ma Z, Dalir H, Khan S. Scaling vectors of attoJoule per bit modulators. Journal of Optics, 2018, 20(1): 014012

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