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- Herausgeber: Wiley-VCH GmbH
- Kategorie: Fachliteratur
- Sprache: Englisch
This book provides recent significant developments of materials and devices for optical imaging and sensing. It covers almost all the aspects related to physical optical sensor.
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Veröffentlichungsjahr: 2023
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Table of Contents
Cover
Title Page
Copyright
Preface
1 Introduction of Optical Imaging and Sensing: Materials, Devices, and Applications
1.1 Optoelectronic Material Systems
1.2 Challenges and Prospect of Nano-optoelectronic Devices
References
2 2D Material-Based Photodetectors for Imaging
2.1 Introduction
2.2 Visible-Light Photodetectors
2.3 Infrared Photodetectors
2.4 Broadband Photodetectors
2.5 Plasmon-Enhanced Photodetectors
2.6 Large-Scale and Flexible Photodetectors
2.7 Summary
References
3 Surface Plasmonic Resonance-Enhanced Infrared Photodetectors
3.1 Introduction
3.2 Brief Review of Basic Concepts of SPR and SPR Structures
3.3 Surface Plasmonic Wave-Enhanced QDIPs
3.4 Localized Surface Plasmonic Wave-Enhanced QDIPs
3.5 Plasmonic Perfect Absorber (PPA)
3.6 Chapter Summary
References
4 Optical Resistance Switch for Optical Sensing
4.1 Introduction
4.2 Graphene Optical Switch
4.3 Nanomaterial Heterostructures-Based Switch
4.4 Modulation Characteristics
4.5 Summary
References
5 Optical Interferometric Sensing
5.1 Introduction
5.2 Nonlinear Interferometer
5.3 Other Types of Nonlinear Interferometers
5.4 Nonlinear Interferometric SPR Sensing
5.5 Summary and Outlook
References
6 Spatial-frequency-shift Super-resolution Imaging Based on Micro/nanomaterials
6.1 Introduction
6.2 The Principle of SFS Super-resolution Imaging Based on Micro/nanomaterials
6.3 Super-resolution Imaging Based on Nanowires and Polymers
6.4 Super-resolution Imaging Based on Photonic Waveguides
6.5 Super-resolution Imaging Based on Wafers
6.6 Super-resolution Imaging Based on SPPs and Metamaterials
6.7 Summary and Outlook
References
7 Monolithically Integrated Multi-section Semiconductor Lasers: Toward the Future of Integrated Microwave Photonics
7.1 Introduction
7.2 Monolithically Integrated Multi-section Semiconductor Laser (MI-MSSL) Device
7.3 Electro-optic Conversion Characteristics
7.4 Photonic Microwave Generation
7.5 Microwave Photonic Filter (MPF)
7.6 Laser Arrays
7.7 Conclusion
Funding Information
Disclosures
References
Index
End User License Agreement
List of Tables
Chapter 2
Table 2.1 Key figures of merit for room-temperature IR photodetectors based ...
Table 2.2 Key figures of merit for advanced broadband photodetectors based o...
Table 2.3 Comparison of plasmon enhancement factors of 2D materials-based ph...
Chapter 3
Table 3.1 Complex permittivity
ε
mr
of gold at different wavelengths.
Chapter 4
Table 4.1 Parameters of the Drude–Lorentz model for silver.
Table 4.2 Mechanism of the heterostructure all-optical switch (Figure 4.13) ...
Table 4.3 Summary of optical structures performance.
Chapter 7
Table 7.1 Comparison of different MISLs including PFLs, AFLs, and MI-MISLs....
Table 7.2 Overview of MISLs for modulation bandwidth enhancement and ROF lin...
Table 7.3 Overview of diverse experimental results optical generation techni...
List of Illustrations
Chapter 1
Figure 1.1 Bandgap versus of lattice constant of group IV, III–V and II–VI s...
Figure 1.2 2D materials with potential applications in different wavelength ...
Figure 1.3 Structure of 2D molybdenum disulfide (MoS
2
) layers. M atoms are i...
Chapter 2
Figure 2.1 Photodetection mechanisms. (a) Photovoltaic effect. (b) Photocond...
Figure 2.2 Electromagnetic spectrum. The wavelength for each region is indic...
Figure 2.3 (a) Schematic 3D view of a MoS
2
photodetector with a local bottom...
Figure 2.4 (a) Perspective and (b) cross-sectional views of a NiO
x
-gated MoS
Figure 2.5 2D/2D and 2D/3D heterojunction photodetectors. (a–c) PdSe
2
/MoS
2
. ...
Figure 2.6 Ultrathin BP-based photodetectors. (a) Schematic of the Si wavegu...
Figure 2.7 2D InSe-based broadband photodetectors. (a) Schematic illustratio...
Figure 2.8 (a–c) Graphene/Si photodetector. (a) Schematic illustration of th...
Figure 2.9 (a) Schematic of localized surface plasmons in metal spheres. (b)...
Figure 2.10 A list of the mechanisms that contribute to the enhanced light a...
Figure 2.11 (a) Schematic illustration of the fabrication processes to integ...
Figure 2.12 (a) Schematic of few-layer plasmon-enhanced MoS
2
phototransistor...
Figure 2.13 (a) Schematic of InSe avalanche photodetector patterned with an ...
Figure 2.14 (a) Schematic diagram showing the growth of SnS
2
2D crystals wit...
Figure 2.15 Graphene/MoS
2
photodetector arrays with strain-induced spectral ...
Figure 2.16 Strain effects on the performance of the photodetector based on ...
Chapter 3
Figure 3.1 Scheme of TM wave incidence on the dielectric and metal interface...
Figure 3.2 Dispersion relationship of the surface plasmonic waves.
Figure 3.3 Surface plasmonic excitation by prism-coupling with the Otto or K...
Figure 3.4 Surface plasmonic excitation by a grating coupler: (a) Schematic ...
Figure 3.5 2DSHA structure for surface plasmonic wave excitation. The 2DSHA ...
Figure 3.6 Simulated transmission of the 2DSHA structures with different per...
Figure 3.7 Simulated
E
-field profile of the 2DSHA structure at a top plane-w...
Figure 3.8 2DSHA structure-enhanced QDIP: (a) Schematic cross-section of the...
Figure 3.9 Comparison of the photocurrents of the 2DSHA structure-enhanced Q...
Figure 3.10 Photocurrents of a different 2DSHA structure-enhanced QDIP (pink...
Figure 3.11 Example snapshot mosaic hyperspectral FPA. The 4 × 4...
Figure 3.12 (a) Schematic structure of the surface current induced in a meta...
Figure 3.13
E
-field distributions of the nanowire plasmonic structure at the...
Figure 3.14 Nanowire plasmonic structure array: (a) schematic view; (b) simu...
Figure 3.15 Simulated for different gap values (pink traces:
g = 0.05 μm
...
Figure 3.16 Localized surface plasmonic waves in circular disk array: (a) sc...
Figure 3.17 Transmission profiles of the circular disk arrays with various d...
Figure 3.18 Resonant wavelengths as a function of the disk diameters. The re...
Figure 3.19 Simulated
E
x
field along the
x
-direction at
y
= 0
....
Figure 3.20 (a) Schematic structure of the perfect absorber; (b) simulated r...
Figure 3.21 Simulated
E
-field in the PPA cavity with the period
p = 4 μm
...
Figure 3.22 Simulated reflection spectra of perfect absorbers with different...
Figure 3.23 Measured photocurrent spectrum of the PPA QDIP compared to that ...
Figure 3.24 (a) Top view of the broadband absorber. Each unit contains circu...
Figure 3.25 (a) Schematic structure of the 2DSHA perfect absorber; (b) simul...
Figure 3.26 Resonant wavelength versus the period of the 2DSHA PPA plot. The...
Figure 3.27 Simulated
E
fields at the
y
= 0 cross section of the 2DSHA PPA c...
Chapter 4
Figure 4.1 General structure of the proposed all-optical graphene plasmon sw...
Figure 4.2 Real and imaginary parts of (a) silver permittivity and (b) graph...
Figure 4.3 (a) Order of the created capacitor layers in Figure 4.1, (b) ligh...
Figure 4.4 (a) GaAs permittivity, (b) variations of the waveguide capacitanc...
Figure 4.5 Main waveguide of the optical switch (Figure 4.1).
Figure 4.6 Field profile of
E
x
at 1.42 μm for...
Figure 4.7 Field profile of
E
x
at 1.42 μm for...
Figure 4.8 Transmission spectrum of main waveguide for (a) the same chemical...
Figure 4.9 The proposed all-optical graphene plasmon switch using a control ...
Figure 4.10 Field profile of
|
H
y
|
for the (a) simple arm and (b) grating arm...
Figure 4.11 Transmission spectrum of the main waveguide for the (a) simple a...
Figure 4.12 Field profile of
|
H
y
|
for the (a) silver arm and (b) vanadium ar...
Figure 4.13 Proposed heterostructure all-optical switch.
Figure 4.14 (a) Proposed structure of 1D PC, (b) its band diagram, and (c) i...
Figure 4.15 Transmission spectrum of the proposed switch (Figure 4.13) (a) f...
Figure 4.16 Transmission spectra of the proposed switch (Figure 4.13) withou...
Figure 4.17 Field profile of
|
E
y
|
at the data wavelength (1429 nm) (a) with ...
Figure 4.18 Transmission spectra of the proposed switch (Figure 4.13) withou...
Figure 4.19 Time-domain representations of (a) data and control signals and ...
Figure 4.20 Proposed heterostructure all-optical switch with the suppression...
Figure 4.21 Time-domain representations of (a) data and control signals and ...
Figure 4.22 Improved proposed heterostructure all-optical switch.
Figure 4.23 Transmission spectrum of the improved proposed switch (Figure 4....
Figure 4.24 Transmission spectra of the improved proposed switch (Figure 4.1...
Figure 4.25 Proposed structure of the designed basic filter.
Figure 4.26 (a) Transmission spectrum of the designed basic filter, (b) zoom...
Figure 4.27 Field profile of Re
(
H
z
)
for the basic filter at the resonance mo...
Figure 4.28 Proposed structure of the all-optical amplitude modulator.
Figure 4.29 Transmission spectra of (a) the proposed modulator (from data in...
Figure 4.30 Field profile of Re
(
H
z
)
at (a) the data wavelength of 878 nm wit...
Figure 4.31 (a) The transmittance of the data wavelength for different value...
Figure 4.32 Time-domain representations of (a) data signal, (b) control sign...
Figure 4.33 Fourier transform of the time-domain output signal for the propo...
Figure 4.34 (a) Proposed structure of the suppression filter and (b) its tra...
Figure 4.35 Field profile of Re
(
H
z
)
at the wavelengths of (a) 702 nm and (b)...
Figure 4.36 Proposed structure of the improved all-optical amplitude modulat...
Figure 4.37 Time-domain representations of (a) data signal, (b) control sign...
Figure 4.38 Fourier transform of the time-domain output signal for the propo...
Chapter 5
Figure 5.1 A nonlinear interferometer with two FWM processes as two equivale...
Figure 5.2 Experimental setup for nonlinear interferometer. PBS, polarizing ...
Figure 5.3 Detailed experimental layout for phase-locking nonlinear interfer...
Figure 5.4 The phase-locking results for BNL method. (a) Signals when scanni...
Figure 5.5 Detailed experimental layout for phase-locking nonlinear interfer...
Figure 5.6 The phase-locking results for CML method. (a) Signals when scanni...
Figure 5.7 The two types of interferometer. (a) MZI and (b) bright-seeded SU...
Figure 5.8 Detailed experimental arrangement. AMP, amplifier; AOM, acousto–o...
Figure 5.9 Typical experimental data and corresponding phase sensitivity for...
Figure 5.10 The phase-sensitivity scaling of the bright-seeded SU(1,1) inter...
Figure 5.11 Scheme of cascaded FWM processes for entanglement enhancement.
Figure 5.12 Group of typical experimental data. See the details in the main ...
Figure 5.13 Experimental and theoretical results of the quadrature squeezing...
Figure 5.14 Typical experimental data. Traces i and ii, quantum noise levels...
Figure 5.15 Experimental and theoretical data for the effect of losses on QN...
Figure 5.16 The schemes of the TSI and NSI. (a) The TSI; (b) the NSI.
Figure 5.17 The comparison of the angular velocity sensitivity versus the an...
Figure 5.18 The angular velocity sensitivity scalings of NSI for the case of...
Figure 5.19 The effect of the losses on the angular velocity sensitivity of ...
Figure 5.20 The effect of the losses on the angular velocity sensitivity of ...
Figure 5.21 Comparison between the scheme of DFWM and the scheme of NDFWM. (...
Figure 5.22 The relationships between the power of two output ports of DFWM ...
Figure 5.23 The dependence of the interference visibilities on various syste...
Figure 5.24 (a) A normal beam splitter combining two beams. (b) A nonlinear ...
Figure 5.25 Experimental layout. (a) ECDL, external cavity diode laser; HWP,...
Figure 5.26 Interference fringes at the output ports of the nonlinear beam s...
Figure 5.27 The intensity ratio and intensity-gain dependence of the two out...
Figure 5.28 (a) The visibilities of the signal and idler fringe as a functio...
Figure 5.29 Observation of
IDS
enhancement. (a) Normalized IDNP spectrum of ...
Figure 5.30 The dependence of
IDS
enhancement on various system parameters. ...
Figure 5.31 (a) An attenuated total reflection prism setup based on the Kret...
Figure 5.32 Nonlinear interferometric SPR sensors. (a) I-type nonlinear inte...
Figure 5.33 (a) The
DS
values of I-type (A) and II-type (B) nonlinear interf...
Figure 5.34 The
DS
values of I-type (A) and II-type (B) nonlinear interferom...
Figure 5.35 (a) The
ℜ
values of I-type (A) and II-type (B) nonlinear i...
Figure 5.36 The
ℜ
values of I-type (A) and II-type (B) nonlinear inter...
Figure 5.37 (a) The
SNR
values of I-type (A) and II-type (B) nonlinear inter...
Figure 5.38 The
SNR
values of I-type (A) and II-type (B) nonlinear interfero...
Chapter 6
Figure 6.1 Mechanisms of evanescent-waves-assisted SFS method. SFS methods s...
Figure 6.2 Evanescent-wave illumination SFS microscopy. (a) Schematic of the...
Figure 6.3 (a) Fabrication procedures for SRCs to produce evanescent waves a...
Figure 6.4 Iterative recovery procedure of TVSFS label-free imaging. The rec...
Figure 6.5 (a) SEM image of multiwall carbon nanotubes (MWCNTs). (b) Optical...
Figure 6.6 (a) The scheme of photonic waveguide for label-free super-resolut...
Figure 6.7 (a) Bending loss of the fundamental mode (the solid line) and the...
Figure 6.8 Conventional SIM and TIRF-SIM use the same objective lens for exc...
Figure 6.9 Large and tunable SFS of STUN in the lateral dimension. (a) Schem...
Figure 6.10 Mechanism of the SFS tuning in vertical dimension based on secti...
Figure 6.11 Physical scheme of chip-based TVSFS super-resolution imaging. (a...
Figure 6.12 Wafer-scale fabrication of a TVSFS super-resolution imaging chip...
Figure 6.13 Simulation of label-free TVSFS imaging. (a) Spatial domain repre...
Figure 6.14 On-chip label-free TVSFS imaging of etched “ZJU” eagle logo. (a)...
Figure 6.15 Resolution calibration of TVSFS label-free imaging using the 561...
Figure 6.16 Resolving fluorescent beads with labeled TVSFS imaging. (a) Diff...
Figure 6.17 Concept of resolution enhancement by structured illumination. Re...
Figure 6.18 Demonstration of resolution improvement in PSIM and LPSIM. (a) S...
Figure 6.19 (a) A HMM-coated substrate projects ultrafine structured speckle...
Chapter 7
Figure 7.1 Scheme of one delayed optical feedback system.
Figure 7.2 Scheme of one PFL, consisting of a DFB section and an IFB section...
Figure 7.3 Multiple schemes of the PFL structure:
Figure 7.4 Reflection spectrum of GR section and transmission spectrum of th...
Figure 7.5 (A) Schemes of the AFL structure. (B) (a) Experimental setup usin...
Figure 7.6 Multiple schemes of MI-MISL structure:
Figure 7.7 (a) The comparison diagram of the enhanced modulation response of...
Figure 7.8 (a) Schematic of ROF link using the laser module, and (b) analysi...
Figure 7.9 IMD3.
Figure 7.10 RF power fading after 40 km SMF.
Figure 7.11 Wavelength difference when fixing one injected current and scann...
Figure 7.12 Calculated beating frequency as functions of feedback strength (...
Figure 7.13 (a) Measured optical spectrum with
I
DC
2
being varied from 60 to ...
Figure 7.14 (a) Electrical spectra measured at the Y-branch facet (with/with...
Figure 7.15 (a) Measured LCMW in one period as well as the calculated instan...
Figure 7.16 Different schematic diagrams with optical-to-electrical/all-opti...
Figure 7.17 Experimentally measured microwave photonic filters
Figure 7.18 Improved characteristics of the four-channel TS-DFB laser, (a) S...
Figure 7.19 The wavelengths of the No. 01 laser in the four-channel TS-DFB-L...
Guide
Cover
Table of Contents
Title Page
Copyright
Preface
Begin Reading
Index
End User License Agreement
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Optical Imaging and Sensing
Materials, Devices, and Applications
Edited by Jiang Wu and Hao Xu
Editors
Prof. Dr. Jiang WuInstitute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, No.4, Section 2, North Jianshe Road, 610054, Chengdu, P.R. China
Prof. Dr. Hao XuSchool of Physics, University of Electronic Science and Technology of China, No.2006, Xiyuan Ave, West Hi-Tech Zone, 611731, Chengdu, P.R. China
Cover Image: © Yuichiro Chino/Getty Images
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Print ISBN: 978-3-527-34976-0ePDF ISBN: 978-3-527-83518-8ePub ISBN: 978-3-527-83519-5oBook ISBN: 978-3-527-83520-1
Preface
To enable conversion between optical and electrical signals, optoelectronic devices that rely on light–matter interactions are gaining much attention and are ubiquitous in modern society. Typically, they can be fabricated using either conventional Si and compound semiconductors (like GaAs, InP, and GaN) or emerging materials, such as graphene, transition-metal dichalcogenides (TMDs), and perovskites, or even using a combination of these materials. Optoelectronic devices for imaging and sensing are integral components of many photon-involved applications, such as optical communications, public security warning, smart city monitoring, clinical imaging, and personal healthcare checking. Considering the rapid development of the Internet of Things, 5G-based techniques, and beyond, optoelectronic imaging and sensing devices are ever increasingly important for these applications. Thereupon, they are facing tough challenges and high demands in terms of device properties and parameters.
High-performance optoelectronic imaging and sensing devices, such as optical sensors, photodetectors, light-emitting diodes (LEDs), lasers, and flexible devices, are indeed desired for practical use. For instance, photodetectors and optical sensors in the near-infrared (IR) and mid-infrared (MIR) regions have a huge number of applications, ranging from telecommunications to molecular spectroscopy. Nowadays, the quest for high photoresponsivity, high detectivity, high photogain, low dark noise, fast photoresponse, and complementary metal-oxide semiconductor (CMOS)-compatible room temperature photodetectors in these spectral regions is ongoing. Moreover, recently there have been significant developments in on-chip integration using emerging two-dimensional (2D) materials and/or plasmonic structures to extend the wavelength range of silicon-based photodetectors beyond 1100 nm. There has also been a lot of interest in building MIR detectors based on 2D material design. In order to achieve further developments based on traditional materials and device structures, new concepts regarding emerging materials and device configuration design can also be adopted. Accordingly, this book covers topics including nanomaterial-based photodetector arrays for imaging, plasmonic photodetectors, optical resistance switches for optical sensing, optical interferometric sensing, novel materials for super-resolution imaging techniques, and nanomaterial advances and on-chip integration.
Chapter 1 describes the material systems and heterostructures for optoelectronics, device components, challenges, and prospects of nano-optoelectronic devices. 2D materials are an expanding family of atomically thin crystals, represented by semimetallic graphene, semiconducting black phosphorus, metallic and semiconducting transition-metal (di)chalcogenides, insulating boron nitride, and so on. They exhibit fascinating characteristics, including tunable bandgap, high carrier mobility, efficient light absorption, good structural stability, and mechanical flexibility. In particular, their excellent photodetecting properties render them attractive for optoelectronic devices. Different strategies have been investigated to further enhance the photodetection capabilities of 2D materials, such as chemical doping, surface modification, defect and strain engineering, and plasmonic nanostructure assisting. Moreover, 2D van der Waals heterostructures have been developed to enrich the optical functionalities, such as fast response over a broad spectral range. Advanced synthesis techniques are desired to realize industrial-scale integration. Chapter 2 focuses on the design and performance of 2D material-based photodetectors for imaging applications.
IR photodetectors and imaging focal plane arrays (FPAs) are critical devices for sensing and imaging applications. Various techniques have been developed to enhance the performance of IR photodetectors and FPAs, including resonant cavities, surface gratings, surface plasmonic resonances (SPRs), optical antennas, and plasmonic perfect absorbers. Chapter 3 reviews the concepts of SPR, its excitation (i.e. resonant conditions), dispersion relations, and near-field profiles and enhancement. The applications of SPR resonance in IR photodetection will also be discussed. Specifically, various SPR structures are discussed, including the metallic 2D sub-wavelength hole array (2DSHA) and localized SPRs in metallic circular disks and nanowires. Plasmonic perfector absorbers (PPA) and their enhancement effect on IR photodetectors will be discussed as well. In Chapter 4, representative publications regarding optical switches for optical sensing applications have been studied. The main properties of the structures are given. Such features are the setup and topology of the optical devices, their mechanism operation, dimensions (2D/3D), and isolated waveguides. Also, whether the time-domain simulations are performed has been investigated. In summary, based on the mentioned properties, these structures have the potential to be used as optical sensors.
In Chapter 5, the nonlinear interferometer is discussed, including experimental implementation of phase locking, enhancement of phase sensitivity, experimental realization of entanglement enhancement, and quantum noise cancellation (QNC). Meanwhile, other types of nonlinear interferometers are described, including a nonlinear Sagnac interferometer, a hybrid interferometer consisting of a nonlinear four-wave mixing (FWM) process and a linear beam splitter, a phase-sensitive FWM process acting as a nonlinear beam splitter, and interference-induced quantum-squeezing enhancement. Afterwards, a nonlinear interferometric SPR sensor has been theoretically proposed and its sensing advantages were demonstrated by using sensing parameters such as degree of intensity-difference squeezing, estimation precision, and signal noise ratio. In Chapter 6, recent achievements of this emerging and fast-growing field have been reviewed. The diffraction limit substantially impedes the resolution of the conventional optical microscope. Under traditional illumination, the high-spatial-frequency light corresponding to the subwavelength information of objects is located in the near-field in the form of evanescent waves and thus not detectable by conventional far-field objectives. Recent advances in micro/nanomaterials and metamaterials provide new approaches to break this limitation by utilizing large-wavevector evanescent waves with the spatial frequency shift (SFS) method. The current super-resolution imaging techniques based on evanescent-waves-assisted SFS method, using nanomaterials, photonic waveguides, wafers, and metamaterials, are illustrated. They are promising in investigating unobserved details and processes in fields such as medicine, biology, and material research.
Recent advances in monolithically integrated multisection semiconductor lasers (MI-MSSLs) have propelled microwave photonic (MWP) technologies to new potentials with a compact, reliable, and green implementation. Much research has examined that MI-MSSLs can realize the same or even better MWP functions compared to discrete lasers by taking advantages of enhanced light–matter interactions. Here, we review these recent advances in this emerging field and discuss the corresponding photonic microwave applications. Three main kinds of MI-MSSL structures are demonstrated in general, including passive feedback laser, active/amplified feedback laser, and monolithically integrated mutually injected semiconductor laser. The focus of this paper is on MWP techniques based on the nonlinear dynamics of MI-MSSLs. The primary MWP applications considered in this paper cover from electro-optic conversion characteristics enhancement, photonic microwave generation, MWP filter, to multiwavelength laser array for wavelength division multiplexing radio-over-fiber (WDM-RoF) networks. Especially, the four special dynamic states of free-running oscillation, mode-beating self-pulsations (MB-SPs), period-one (P1) oscillation, and sideband injection locking are considered and demonstrated in detail for photonic microwave generation. In Chapter 7, the authors take a look at the future prospects of the research directions and challenges in this area.
We acknowledge all the contributors and sincerely hope this book can help readers better understand materials, devices, and applications for optical imaging and sensing.
Chengdu, China28 December 2022
Hao Xu
Jiang Wu
University of Electronic Science and
Technology of China
1Introduction of Optical Imaging and Sensing: Materials, Devices, and Applications
Qimiao Chen1 Hao Xu2 and Chuan S. Tan1
1Nanyang Technological University, School of Electrical and Electronic Engineering, Singapore, 639798, Singapore
2University of Electronic Science and Technology of China, School of Physics, Chengdu, 610054, China
1.1 Optoelectronic Material Systems
Typically, optoelectronic devices for sensing and imaging can be fabricated by either group IV (Si, Ge, Sn, and their alloys) or compound semiconductors (like GaAs, InP, and GaN). Recently, there have been significant developments in on-chip integration using emerging two-dimensional (2D) materials and/or plasmonic structures to extend the wavelength range of silicon-based photodetectors beyond 1100 nm.
1.1.1 Si Platform
Si is not only the dominant material for the modern Information Age (also known as Silicon Age), which is driven by Si electronics, but also one of the most promising platforms for photonics to construct sensing or imaging systems. Si photonics, which is compatible with the current Si electronic industry, will share the benefits of Si technologies in terms of monolithic electronic–photonic integration, scaling, and low cost, which may result in a Si-based optoelectronic revolution in the future. Si photonics have been developed for various applications in the near-infrared (NIR) and shortwave infrared (SWIR) ranges.
Si photonics is a rapidly developing field. Recently, it has achieved a breakthrough with Ge-related materials (SiGeSn). As shown in Figure 1.1, the SiGeSn material system has some interesting optical properties that are ideal for constructing optoelectronic devices for sensing and imaging: (i) the lattice constant and bandgap can be tuned independently to form high-quality heterostructures to control the carriers; (ii) bandgap can be converted from indirect to direct; (iii) coverage of NIR, SWIR, and mid-infrared (MIR) wavelengths; (iv) the compatibility of growth temperature (<400 °C) with complementary metal oxide semiconductor (CMOS) process; and (v) high mobility, low Auger, and nonpolar.
Figure 1.1 Bandgap versus of lattice constant of group IV, III–V and II–VI semiconductors.
Source: Reproduced with permission from Moutanabbir et al. [1].
Early proposals to utilize SiGeSn materials for photonics date back to the 1990s. However, the actual development of practical devices has been hampered by the technical challenges of growing high-quality SiGeSn materials. While the thermal expansion coefficient mismatch between the epitaxial layer and Si substrates showed a positive effect on the epitaxial Ge layer, the large lattice mismatch between the elements (4.2% for Ge and Si, 14.7% for Sn and Ge, and 17% for Sn and Si) makes the grown layer tend to be defective and rough. For example, when the Ge or GeSn layer is epitaxially grown on Si substrates, misfit will inevitably be generated at the interface and propagate to the surface of the epitaxy layer as threading dislocations, which degrades the material quality and hinders the practical application of Ge or GeSn optoelectronic devices. Besides, it is challenging to incorporate Sn into Ge due to the extremely limited solid solubility of Sn (<1% in Ge), and Sn is prone to segregation at higher concentrations and growth temperatures. Therefore, GeSn alloys are unstable and require nonequilibrium growth. Fortunately, the device-level-quality SiGeSn materials have been grown recently by molecular beam epitaxy (MBE) or chemical vapor deposition (CVD) with various Ge and Sn precursors. We will introduce the growth of GeSn alloys and Ge by commercial CVD systems, which are of higher material quality and compatible with the industry for mass production.
To solve the first issue of lattice constant mismatch between epitaxial layers and Si substrates, relentless efforts have been made. Using a fully relaxed, thick-graded buffer layer can reduce the lattice constant mismatch between the Ge epitaxial layer and Si substrate. However, this method suffers from the issue of wafer bow as the graded buffer layer is usually too thick (∼10 μm), so it could not be grown by industrial CVD tools. The second approach is the selective area growth (SAG) technique. The Si substrate is patterned, followed by epitaxial lateral overgrowth. Threading dislocations do not slide parallel to the growth direction, and they can slide to the window sidewalls and annihilate. The third more practical approach is the two-step growth method. A thin Ge seed layer was grown at low temperatures to restrict the mobility of Ge adatoms, thereby preventing 3D nucleation of Ge. Afterward, a thick Ge film is grown under high-temperature conditions for a higher growth rate and better Ge crystallinity.
For the growth of (Si)GeSn alloys, currently, the main Sn precursors are tetramethyl tin [Sn(CH3)4] and stannic chloride (SnCl4). The main Ge precursors are GeH4, Ge2H6, and Ge3H8. There are two approaches to obtaining GeSn layers with high Sn concentrations: (i) the spontaneous relaxation-enhanced (SRE) Sn incorporation process and (ii) the GeSn virtual substrate approach. When GeSn is grown on a Ge buffer using a fixed Sn concentration recipe, the Sn concentration will increase from the GeSn/Ge interface to the GeSn surface due to the strain relaxation. Thus, the grown layer will normally show two distinct layers, with the first strained layer being defective and the second relaxed layer having low defect density. Using the GeSn layer obtained by the SRE method as the virtual substrate to grow GeSn layers, an Sn concentration of up to 22.3% has been achieved. In addition to GeSn or Ge on Si substrates, some advanced engineered substrates, such as Ge(Sn) on insulator (GOI) and Ge on SiN (GON), have been proposed for the benefits of the smaller device area, increased packaging density, and high mobility.
Since the breakthrough in material growth, many devices have been developed for silicon photonics, including light emitters, amplifiers, photodetectors, waveguides, modulators, couplers, and switches. Progress has also been made in the most challenging components of Si light sources, and a complete set of components is being delivered for silicon photonics.
1.1.2 Two-dimensional Materials and Their van der Waals Heterostructures
Graphene was discovered in 2004 and the discoverers won the Nobel Prize due to its attractive 2D properties. Since then, many atomically thin 2D layered materials have been discovered, ranging from metallic (graphene and TaSe2), semiconducting (WSe2 and MoS2), superconducting (NbSe2 and FeSe) to topological insulators (Bi2Se3 and Sb2Te3). Through the combination of quantum confinement and enhanced electronic interactions, these atomically thin materials become strongly renormalized. Besides, different 2D materials can form various heterostructures by weak van der Waals forces. Figure 1.2 illustrates the available 2D materials and their electronic band structures covering a wide range of the electromagnetic spectra, from ultraviolet, visible, infrared to microwave, which would have different applications such as sensing, optical communication, and thermal imaging. We will introduce the properties of some typical individual 2D materials, followed by their van der Waals heterostructures.
1.1.2.1 Graphene
Graphene is a zero-gap semimetal with a single layer of 2D honeycomb carbon atoms. The resistivity will be reduced exponentially by adding electron/hole carriers. The interaction of the surrounding electrons around the honeycomb carbon atoms leads to the quasiparticles of massless Dirac fermions. Graphene has many attractive properties, such as high electron mobility (up to 2.5 × 105 cm2 V−1 s−1), high thermal conductivity (>3000 W mK−1), high intrinsic strength of 130 GPa, and Young's modulus of 1 TPa.
Figure 1.2 2D materials with potential applications in different wavelength regimes.
Source: Reproduced with permission from Castellanos-Gomez [2].
1.1.2.2 Transition Metal Dichalcogenides
Transition metal dichalcogenides are atomically thin semiconductors with the formula MX2, with M, a transition metal element (Mo, W, or Nb), and X, a chalcogen element (S, Se, or Te). A pane of transition metal atoms is sandwiched by two layers of chalcogen atoms, as shown in Figure 1.3. The electrical and optical properties can be tuned by incorporating different transition metal elements. Transition metal dichalcogenides (TMDs) can vary from semiconducting to metallic characteristics, and some even demonstrate superconductivity characteristics (NbS2 and TaSe2).
Figure 1.3 Structure of 2D molybdenum disulfide (MoS2) layers. M atoms are in grey and X atoms are in yellow.
Source: Reproduced with permission from Jariwala et al. [3].
Among various TMDs, MoS2 is a semiconductor with an indirect bandgap of 1.3 eV. The MoS2 will be converted into a direct bandgap with an energy of 1.8–1.9 eV when it is reduced to a monolayer, which is proved by photoluminescence (PL) measurements. Modified MoS2 has demonstrated the ability to maintain permanent valley polarization, which is promising for valleytronics. Monolayer MoS2 is also a candidate for spintronics due to its strong spin-orbit splitting. Monolayer TMDs have been applied in high-efficiency 2D optoelectronics devices such as light-emitting diodes (LEDs) and lasers.
1.1.2.3 2D Heterostructures
Within the wide range of materials available, the ways in which they can be combined are virtually limitless, each with its own unique properties and phenomena. For example, a tunneling device demonstration uses a thin layer of insulating hBN as a tunnel barrier between graphene sheets. 2D quantum wells can be formed by sequentially stacking different semiconducting transition metal dichalcogenides. Graphene/hBN heterostructure has been used to fabricate tunable LEDs. The development of nanoscale metamaterials has been achieved by coupling 2D materials with repeating nanostructures, revealing interesting plasmonic properties. The demonstrated applications of 2D heterostructures are in the fields of light detection, light generation, electronics, and some emerging directions such as single-photon emitters, quantum dot qubits, superconducting qubits, and topological quantum computing components.
1.2 Challenges and Prospect of Nano-optoelectronic Devices
Miniaturization of optoelectronic devices to the nanoscale offers enormous performance gains. As the volume of photoactive materials decreases, optoelectronic performance increases, including the operating speed, signal-to-noise ratio, and internal quantum efficiency. Over the past decades, the volume of photoactive materials in optoelectronic devices has been reduced by orders of magnitude. Relentless efforts have been made to overcome the limitations of further miniaturization. Among them, replacing Si with a new class of nanomaterials, such as 2D materials or heterostructures, is a promising candidate method. However, due to the lack of scalable fabrication methods, this direction is mostly limited to proof-of-concept research. Efforts are made toward the scalable fabrication of 2D heterostructures. CVD and metal organic chemical vapor deposition (MOCVD) are promising candidate methods. Nonetheless, the growth kinetics has not been fully understood. Large-scale and high-quality 2D HS with high controllability is also needed. Besides, the environmental stability of the device is a great challenge. To enable further development of nanodevices, new concepts regarding emerging materials and device configuration design need to be employed. Accordingly, the book will cover topics including (i) nanomaterials-based photodetector arrays for imaging, (ii) plasmonic photodetectors for sub-wavelength photodetection, (iii) optical resistance switch for optical sensing, (iv) optical interferometric sensing, (v) novel materials for clinical applications, (vi) computational imaging/sensing based on nanomaterials, and (vii) nanomaterial advances and on-chip integration.
1.2.1 III–V Compounds
Si is the most widely used semiconductor material due to its rich reserves, mature technology, and low cost, but it has an indirect band gap. Compared with Si, III–V compound semiconductors (such as GaAs, InP, GaN, and GaSb) and their alloys have direct band gaps. That is to say, the top of the valence band and the bottom of the conduction band are located at the same position in the wave vector space, and the electron–hole recombination does not need to exchange momentum, so it has high internal quantum efficiency and is predominantly used in optoelectronic devices [4].
GaAs is a typical III–V compound semiconductor material and is widely used in many optoelectronic fields, such as remote control, mobile phones, and lighting. Its band gap width is 1.42 eV (300 K), which can just absorb the high-energy part of the solar spectrum. Therefore, it is an ideal material for preparing solar cells. Researchers from the US Department of Energy's National Renewable Energy Laboratory (NREL) have developed a six-junction III–V solar cell with a 47.1% conversion efficiency rate under 143 suns of concentration. Its quaternary systems InGaAsP and InGaAlAs just cover the O band (1260—1360 nm, 1310 nm in the center) or C + L band (C band: 1530—1565 nm, 1550 nm in the center; L band: 1565—1625 nm) commonly used in optical communication. InxGa1−xAs photodetector can be used from 400 to 3600 nm, which is suitable for a wide range of applications, including optical communication, analysis, and measurement. Flexible InGaAs thin film materials have great potential in optoelectronic field. For practical fiber quantum key distribution (QKD), InGaAs/InP avalanche photodiodes are the NIR light detector of choice because they are compact and low cost, and allow cryogenic-free or even room-temperature operation [5].
Direct epitaxy on silicon is the most direct method to produce III–V compound semiconductors. However, the lattice mismatch between silicon and III–V compounds is very large (the mismatch between silicon and GaAs and InP is 4% and 8%, respectively), and this causes strain in the materials. In addition, silicon is a nonpolar crystal, whereas III–V compounds are polar. When the two are combined, an antiphase domain will exist at the interface. Therefore, obtaining high-quality epitaxial layers of III–V materials directly determines the performance of semiconductor optoelectronic devices. To solve these problems, buffer layers are usually introduced to reduce the defect density caused by the growth of III–V semiconductors on silicon. For example, the mismatch between Ge and GaAs is 0.08%, and the thermal expansion coefficient is relatively close. In order to suppress the antiphase domain, a silicon substrate with a certain deflection angle can be used, and the substrate can be pretreated at high temperature in the gas of V group elements. By this method, the diatomic steps can be formed on the silicon substrate and the surface reconstruction can be realized, which can suppress the antiphase domain.
1.2.2 Perovskites
Perovskite is a crystal material with the general molecular formula ABX3, which is octahedral in shape and has excellent structural properties. Perovskites have been intensively studied in many fields and applications owing to their excellent photoelectric efficiency and PL [6]. Especially as a promising photoelectric material, they have a wide range of applications in perovskite photovoltaic (PV) cells, LEDs [7, 8], low-threshold lasers [9, 10], electroluminescent devices [11–13], photodetectors [14], and photocatalysts [15]. Perovskite structure has strong designability and excellent photovoltaic performance, which has been a hot research direction in photovoltaics in recent years. Due to their high PL quantum efficiency, perovskites were reported as potential luminescence probes for cell imaging after overcoming the challenge of hypertoxicity by external encapsulation. Perovskite structure material is an important development path for next-generation LEDs for lighting or display. Perovskite is also the representative of the third-generation high-efficiency thin-film battery. In particular, organic perovskite is considered as a promising optoelectronic photoelectric semiconductor material. The explorations in photoelectric devices and bioscience broaden the application of perovskite. However, due to the difficulty in repetitively preparing high-quality perovskite thin films, low coupling efficiency of optical output, lead pollution, and other problems, there is still a certain distance from commercial application.
1.2.3 Organic Optoelectronic Materials
Organic optoelectronic materials are usually organic molecules rich in carbon atoms with large π-conjugated systems, which can be divided into four categories: conjugated conducting polymers, organic conjugated small molecules, phosphorescent heavy metal complexes, and aggregation-induced enhanced luminescence materials. Compared with inorganic optoelectronic materials, organic optoelectronic materials have lower costs, are thin in thickness, are light in material, and usually with higher light absorption coefficient. The material manufacturing process is simple and can be prepared in large areas and on flexible devices by solution method. In addition, organic materials have diversified structure compositions and wide property manipulation, which can obtain the required performance through molecular design. We can prepare nanodevices and molecular devices through bottom-up device assembly methods such as self-assembly. Organic optoelectronic materials are mainly used in organic solar cells, organic LEDs (OLEDs), and other display screens. Organic light-emitting materials are the key core materials of OLED panels, which directly determine the luminous characteristics of panels and are also one of the areas with the highest technical barriers. The application of organic optoelectronic materials in biomedicine has developed from early biosensors and detection to biological imaging and tumor treatment in recent years, especially high-resolution photoacoustic imaging and NIR imaging, providing a new method for the diagnosis of brain tumors and vascular tumors. Organic photovoltaics (OPV) will become an excellent candidate for energy supply on the Internet of Things (IoT) and intelligent wearable devices because of its unique mechanical flexibility, printability, and adjustable light absorption. However, organic photoelectric materials also have many disadvantages, such as low photoelectric conversion efficiency, short life, low mobility of carriers, high resistance, and poor durability. In addition, the synthesis steps of organic optoelectronic materials are cumbersome and not suitable for large-scale production. In organic semiconductors, the diffusion length of excitons is generally short, ranging between 10 and 20 nm [16]. This reduces efficiency, since the electrons accumulated as a result of solar energy conversion cannot easily flow through the photovoltaic semiconductor. Many of the advantages of organic solar cells are overridden by their relatively low efficiency, since this is the most important factor with respect to electricity generation by the cell.
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22D Material-Based Photodetectors for Imaging
Wenshuo Xu1,2,3, Zhuo Wang1 and Andrew T. S. Wee2,4
1Shenzhen University, SZU-NUS Collaborative Innovation Center for Optoelectronic Science & Technology, International Collaborative Laboratory of 2D Materials for Optoelectronics Science and Technology of Ministry of Education, College of Optoelectronic Engineering, 3688 Nanhai Street, Shenzhen Guangdong, 518060, China
2National University of Singapore, Department of Physics, 2 Science Drive 3, Singapore, 117551, Singapore
3University of Cambridge, Department of Materials Science and Metallurgy, 27 Charles Babbage Road, Cambridge, CB3 0FS, United Kingdom
4National University of Singapore, Centre for Advanced 2D Materials, 6 Science Drive 2, Singapore, 117546, Singapore
2.1 Introduction
Advanced photodetectors play an important role in high-quality imaging. Figure 2.1 shows the key photodetection mechanisms. The photocurrent can be generated either by the excitation of charge carriers or by the heat produced as a result of exposure to light. In the former case, the optical transition is ascribed to photovoltaic, photoconductive, or photogating effect. The photovoltaic effect occurs when the energy of the absorbed photons is greater than the bandgap, so that the electron–hole pairs are excited and separated under the built-in electric field at the metal–semiconductor junction or p–n heterojunction (Figure 2.1a). The photoconductive effect refers to the situation where the photoinduced carriers lead to an increased density of charges and a decreased resistance of the semiconducting material. The excess carriers are drifted in the presence of applied bias, thereby forming photocurrent (Figure 2.1b). As a particular example, the photogating effect happens when the photocarriers are localized at the surface or defect sites of the semiconductor. Their trap states act as a gate, regulating the conductance of the channel. Light irradiation can also increase the temperature of photoactive materials. The photobolometric effect originates from uniform temperature change (ΔT) across the channel. The sign of the photocurrent is dependent on the induced variation in the resistivity, which is a function of temperature (Figure 2.1c). The photothermoelectric effect would happen if the light is illuminated at the junction of two materials with different thermoelectric properties or if the spot size of the incident light is smaller than the channel width (Figure 2.1d). A temperature gradient can be formed when the photon absorption is uneven across the channel, giving rise to a photovoltage and driving a current through the detector. The sign of the photocurrent is related to the carrier polarity and the difference of Seebeck coefficients between the adjacent illuminated regions. The driving force to form a potential difference is built-in electric field for photovoltaic effect, while it is temperature gradient for the photothermoelectric effect. Both of them are based on the spontaneous transport of electrons and holes toward the two ends of the channel, offering access to self-driven photoresponse. In contrast, for photoconductive, photogating, and photobolometric effects, the photocurrent cannot be generated without an external bias voltage.
Figure 2.1 Photodetection mechanisms. (a) Photovoltaic effect. (b) Photoconductive effect. (c) Photobolometric effect. (d) Photothermoelectric effect. S1 and S2 represent two semiconductors with different thermoelectric properties.
The performances of photodetectors are evaluated by several figure-of-merits, including photoresponsivity (R), external quantum efficiency (EQE), photoconductive gain, response speed, detectivity (D), or specific detectivity (D*), and so on. R is the ratio of photogenerated voltage or photocurrent to the incident light power, expressed as R = Iph/Pin, where Iph represents the photocurrent and Pin is the power of the incident light. Its value depends on the light wavelength because the photon absorption is correlated with the bandgap of the semiconductor. EQE is the number of collected electron–hole pairs divided by the number of incident photons, i.e. EQE = (Iph/e)/(Pin/Eph), where e is the charge of an electron and Eph is the energy of a photon. Photoconductive gain evaluates the capability of a photodetector in generating charge carriers in response to a single photon. Response speed is usually characterized by the rise and decay/fall times with the light pulse switched on and off, i.e. the time intervals needed for the output signal to increase from 10% to 90% and decrease from 90% to 10% of its on-state maximum, respectively. D is defined as the inverse of the noise-equivalent power. Its normalization result to the active detecting area and the detection bandwidth, known as D*, has been widely used to quantify the sensitivity of a photodetector to signals against the noise. D* = R/(2eJd)1/2, where Jd is the dark current density, and the unit is Jones or cm Hz1/2 W−1.
The detection range is categorized according to the light wavelength. The absorption spectrum includes ultraviolet (UV) (10–400 nm), visible (400–750 nm), infrared (IR, 0.75–30 μm), and terahertz (THz) (30 μm to 3 mm) bands. Specifically, the UV range is further divided into UV-A (320–400 nm), UV-B (280–320 nm), and UV-C (100–280 nm), and the IR range is further divided into near-infrared (NIR, 750 nm to 3 μm), mid-infrared (MIR, 3–5 μm), long-wave infrared (LWIR, 8–12 μm), and very long-wave infrared (VLWIR, 12–30 μm). The full electromagnetic spectrum is shown in Figure 2.2, where the visible region is specified. For certain incident light, it is important to choose a photodetector with appropriate response wavelength. In Sections 2.2, 2.3 and 2.4, we will discuss about the visible, IR, and broadband photodetectors that are composed of two-dimensional (2D) materials.
Traditional thin-film materials fail to meet the increasing demands of modern device manufacture because of the limited detection wavelength, strict working conditions, high cost, and difficult fabrication. For instance, electronics and optoelectronics based on silicon play a leading role in the integrated circuit industry. However, the indirect energy gap of silicon (1.12 eV) constricts its response to light within the visible–NIR regime [1]. GaAs and InSb have been employed for IR photodetectors, which often operate at cryogenic temperatures [2, 3], while the cooling requirement increases the expense and volume of the systems. Other examples include InGaAs and HgCdTe thin films, the growth procedures of which are complicated [4]. Therefore, it is necessary to develop some alternatives to overcome the above challenges.
Figure 2.2 Electromagnetic spectrum. The wavelength for each region is indicated.
A variety of 2D materials-based photodetectors have been reported in the past few years, including graphene, transition-metal chalcogenides (TMCs), transition-metal oxides (TMOs), black phosphorus (BP), arsenic phosphorus (AsP), and indium selenide (InSe). They can also form van der Waals heterostructures without the limitation of lattice matching. Many of these materials can interact with light and convert the photons to an electrical signal dictated by their unique band structures. Although graphene has large electron mobility (≈105 cm2 V−1 s−1), only ≈2.3% of the incident visible and IR light can be absorbed in monolayer thickness [5]. Furthermore, the zero-gap of graphene results in short lifetime of the photoinduced carriers, which are not favorable for efficient yield of photocurrents. As compared with graphene, the van Hove singularities in 2D transition metal dichalcogenides (TMDs) contribute to stronger light–matter interactions in visible and IR light ranges, and their tunable band gap by varying their layer number allows the detection of light with different wavelengths [6]. A promising method to exploit the properties of both graphene and TMD is to create hybrid devices where graphene is used as the electrodes and TMD acts as the photoactive channel. Moreover, owing to the atomic thickness and absence of dangling bonds, 2D materials often exhibit fast carrier transport and outstanding gate modulation ability. Previous works have demonstrated that 2D materials and their heterostructures are superior to conventional semiconducting materials in terms of the spectral coverage, mechanical flexibility, transparency, ease of processing, etc.
High photoresponsivity, fast response, low dark current, and large ON/OFF ratio are highly desired for advanced photodetectors. However, some pristine 2D materials cannot meet such demands. To enhance the device performance, several methods have been proposed [7]. Quick charge extraction is believed to assist the photodetection. For example, contacting the semiconductor with highly conductive 2D layers, usually graphene, accelerates the separation of electrons and holes, and reduces the contact resistance. Another strategy is building up vertical 2D TMD heterostructures to modify the band structure and match the cutoff wavelength of the incident light. In these heterostructures, adding a dielectric barrier layer can reduce the dark current and therefore improve the detectivity. In addition, plasmonic nanostructures, which support surface plasmons, can strengthen the light–matter interaction in materials, so they are used to improve the photoresponsivity of photodetectors based on 2D materials. Regarding the preparation methods, chemical vapor deposition (CVD) and molecular beam epitaxy are advantageous in producing clean interfaces. The strong interlayer coupling guarantees efficient charge transfer across the heterojunction. In addition to the structural design and performance improvement of 2D materials-based photodetectors, recent studies also focus on their large-scale manufacturing from single to arrayed devices and extension of their detection range from narrowband to broadband. All of these aspects are crucial for the development toward imaging applications and hence will be covered in this chapter.
2.2 Visible-Light Photodetectors
Silicon and germanium compounds with bandgaps of ≈1 eV have been used for visible-light photodetectors. Nevertheless, short-channel effects often take place when the channel length is approximately equal to the depletion layer widths of the source and drain junctions. Typical resultant phenomena may include barrier lowering, velocity saturation, quantum confinement, and hot carrier degradation [8]. In addition, the manufacturing costs of Si and Ge semiconductors are relatively high. These disadvantages have restricted the further miniaturization and large-scale integration of conventional photodetectors. The absorption wavelengths of many 2D TMDs are also in the visible-light spectrum, such as molybdenum dichalcogenides (MoX2, X = S, Se, Te), tungsten dichalcogenides (WX2, X = S, Se), tin dichalcogenides (SnX2, X = S, Se), gallium chalcogenides (GaX, X = S, Se, Te), and indium selenides (InSe, In2Se3). They can thus be promising supplements to the traditional materials and have attracted much research interest.
The earliest demonstration of a 2D TMD-based phototransistor was reported by Yin et al. in 2012 [9]. Utilizing mechanically exfoliated monolayer MoS2 as the channel, the device exhibits a photoresponsivity of 7.5 mA W−1 upon laser excitation at 488 nm with a response time of ≈50 ms. Follow-up studies were centered on the factors affecting the photoresponse [10].
First, the photoresponsivity is influenced by the external conditions, including the incident light wavelength, excitation power density, and applied electric field. The absorption of light is dependent on the intrinsic energy-band structure and absorption coefficient of semiconducting materials. When the photon energy is larger than the bandgap, photocarriers, i.e. electron–hole pairs, are formed via the transition of electrons from the valence band to the conductance band. An increase in the concentration of photocarriers due to the enhanced absorption corresponds to a higher responsivity. Although more photocarriers can be produced as the excitation power increases, the reduced efficiency of carrier excitation and the enhanced Coulomb scattering may have a dominant effect on the generation of photocurrent. Therefore, the responsivity generally decreases with increasing light power density. The power dependence can be explained by Auger recombination, i.e. a nonradiative process in which electron–hole pairs recombine and give off energy to another electron in the same conduction band [11]. This effect is enhanced at high power density. It influences the lifetime of photocarriers and, thus, the efficiency of the device. Implementation of a gate bias can vary the carrier density in the semiconductor via modulation of the Fermi surface. This enables restriction of the dark current and improvement in the responsivity.
Second, the responsivity is dependent on the layer number of TMDs. Changing their layer number can modulate the bandgap and hence tune the response wavelength of the photodetector. For example, the bandgap of BP shows direct characteristics. Its value increases from ≈0.35 eV for the bulk to ≈2.0 eV for the monolayer [12]. Many TMDs also present increasing bandgaps as the layer number decreases, yet unlike BP, they undergo an indirect-to-direct transition when thinned down to the monolayer limit as a result of quantum confinement effects [13]. The layer-dependent bandgap dictates the cutoff wavelength in the absorption spectrum and influences the photodetection range. Lee et al. studied top-gate phototransistors based on mono-, bi-, and three-layer MoS2 flakes. Mono- and bi-layer MoS2 with optical energy gaps of 1.82 and 1.65 eV, respectively, exhibit maximal photoresponse in the red-light spectrum, whereas three-layer MoS2 with an optical energy gap of 1.35 eV shows the best green-light detection capability [14]. Increasing thickness within a certain range often leads to enhanced optical absorption and responsivity. 2D ReS2 has a direct band gap with a constant value (1.5 eV) irrespective of its layer number. The photodetector based on 30-nm ReS2 can reach a high responsivity of 2.5 × 107 A W−1, which is among the record-high values achieved by 2D materials [15]. This outstanding performance can be attributed to the combination of the relatively large thickness and the direct bandgap, which brings enhanced light absorption. As in other special cases, bulk PtS2 and PtSe2 are semimetals, whereas they become semiconductors with bandgap opening at reduced thicknesses below a few nanometers (≈3 nm for PtS2 and ≈4 nm for PtSe2). These enable photodetection in visible-light spectrum [16, 17].
Third, the photoresponse of TMDs is influenced by charge trapping in the TMD layers or at the TMD–substrate interface. Kufer and Konstantatos [18] encapsulated monolayer and bilayer MoS2 with atomic layer-deposited HfO2
