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J. Semicond. > 2025, Volume 46 > Issue 1 > 011602

REVIEWS

Design strategies and insights of flexible infrared optoelectronic sensors

Yegang Liang, Wenhao Ran, Dan Kuang and Zhuoran Wang

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 Corresponding author: Zhuoran Wang, Zhuoran.wang@bit.edu.cn

DOI: 10.1088/1674-4926/24080044CSTR: 32376.14.1674-4926.24080044

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Abstract: Infrared optoelectronic sensing is the core of many critical applications such as night vision, health and medication, military, space exploration, etc. Further including mechanical flexibility as a new dimension enables novel features of adaptability and conformability, promising for developing next-generation optoelectronic sensory applications toward reduced size, weight, price, power consumption, and enhanced performance (SWaP3). However, in this emerging research frontier, challenges persist in simultaneously achieving high infrared response and good mechanical deformability in devices and integrated systems. Therefore, we perform a comprehensive review of the design strategies and insights of flexible infrared optoelectronic sensors, including the fundamentals of infrared photodetectors, selection of materials and device architectures, fabrication techniques and design strategies, and the discussion of architectural and functional integration towards applications in wearable optoelectronics and advanced image sensing. Finally, this article offers insights into future directions to practically realize the ultra-high performance and smart sensors enabled by infrared-sensitive materials, covering challenges in materials development and device micro-/nanofabrication. Benchmarks for scaling these techniques across fabrication, performance, and integration are presented, alongside perspectives on potential applications in medication and health, biomimetic vision, and neuromorphic sensory systems, etc.

Key words: flexibleinfrared sensorinfrared-sensitive materialsdevice architecturesfabrication techniquesdesign strategies

In recent years, micro-electro-mechanical system (MEMS) devices are rapidly developed with the advances of science and technology. Among them, MEMS gyroscopes are playing an increasingly important role in inertial navigation applications owing to the advantages of small volume, low cost, low power consumption and so on[13]. The MEMS gyroscope is the sensor that measures the rate of rotation of an object[4] based on the Coriolis effect. It is a kind of active device, which requires both actuation and detection mechanisms. The most common actuation method and Coriolis response detection technique are electrostatic actuation and capacitive sensing, respectively. The stability of the resonant frequency is one of the most basic characters for gyroscopes.

However, it is an extremely challenging work to make such devices highly reliable. Some researchers have observed that the resonance frequency can drift either due to mechanical changes of the resonator[5] or due to charging[6]. The frequency drifts due to charging have a relation with DC voltage bias which, in general, is required for the electrostatic actuation of the MEMS devices[7].

It has been reported that many MEMS devices such as micro switches, micro resonators and micro mirrors all suffer from dielectric charging problems[810]. In this paper, we study the mechanism and variation of the parasitic charge in the MEMS gyroscopes, and analyze the effect of the parasitic charge on the output stability. Firstly, we briefly introduce the working principle of the gyroscopes in Section 2.1. Next in Section 2.2, we analyze the effect of the frequency drift due to the parasitic charge accumulation on the output of the gyroscopes in theory. Finally, we experimentally demonstrate that the parasitic charge is harmful to the output stability of MEMS gyroscopes in Section 3.

In this section, we introduce the working principle of vibratory gyroscopes and the effect of the frequency drift on the output of the gyroscopes.

We take linear vibratory gyroscopes for example. The basic architecture of a vibratory gyroscope is comprised of a drive-mode oscillator that generates and maintains a constant linear momentum, coupled to a sense-mode Coriolis accelerometer that measures the sinusoidal Coriolis force induced due to the combination of the drive vibration and an angular rate input[4]. Simply it can be equivalent to a mass-spring-damper model in both drive and sense directions. For a closed-loop drive and open-loop sense scheme, the equations of motion of the resonator are

mxd2xdt2+cxdxdt+kxx=F0sinωdt, (1)
myd2ydt2+cydydt+kyy=2Ωzmcdxdtkyxx, (2)

where mx, my and mc are the proof-mass of the drive mode, sense mode and the portion of the drive mode that contributes to the Coriolis force, kx and ky are the stiffness of the drive and sense mode, while cx and cy are damping factors of the drive and sense mode, respectively. F0 is the amplitude of a harmonic force with the frequency ωd (usually equals to the resonant frequency of drive mode ωx). In the y direction, the displacement of the proof-mass contains the rate signal and quadrature error. The former is related to the input Ωz and the latter is related to the coupling stiffness kyx resulting from fabrication imperfections[4]. They are orthogonal so that can be extracted by demodulation. The steady-state component of the response is also harmonic, of the form

x=x0sin(ωdt+φd), (3)
y=y1cos(ωdt+φy)+y2sin(ωdt+φy), (4)

where x0 and φd are the amplitude and phase of the drive mode, y1 and y2 are the amplitude of the displacement induced by rate signal and quadrature error respectively, while φy is the phase of the sense mode output. When Ωz = 0, y1 = 0, then the output is called ZRO (zero rate output). The ZRO is

uZRO=12kyxx0/my(ωy2ωd2)2+ωy2ωd2/Qy2×sin[arctanωyωdQy(ωy2ωd2)φd], (5)

where ωy and Qy are the resonant frequency and quality factor of the sense mode. It is shown that the ZRO is affected by ωy which is a time-dependent variable determined by dielectric parasitic charges. We will discuss this problem in detail in the next section.

The model in Fig. 1 shows a device that is actuated by the electrostatic force. The bias voltage V will soften the resonant element and generate a negative stiffness effect[1113].

Figure  1.  The parallel-plate electrodes that generate electrostatic force.

According to the deduction in Ref. [11], the variation of stiffness caused by the bias voltage could be expressed as

Δk=xzy3ε0V2. (6)

where x, y, z are dimensions in three directions, ε0 is the air permittivity and V is the bias voltage.

The dielectric layer in MEMS devices is created either by a natural chemical reaction like oxidation or by artificial means to achieve a certain function (such as Pyrex substrate). In the dielectric layer, the parasitic charge would accumulate due to the DC voltage required for the device operation. The physical mechanisms of the charging phenomena are not fully understood, yet it can be illustrated with a contactless or contact model[8]. Polarization and migration will occur in both models. Besides, in the contact model, the dielectric layers and the electrodes are adhesive to each other, while ion injection is another charging mechanism[1418]. All of these three charge movements can interrupt the internal balance of the electric field and form an extra electrostatic force on the MEMS devices. These charge behaviors in dielectric materials are considered to be the main cause of drifting of many micro devices, such as accelerometer, micro switch, micro resonators, micro mirrors and so on.

In the capacitive MEMS device shown in Fig. 3, a dielectric layer of thickness d and of charge density ρ will induce a built-in voltage. We can use the simple model in Fig. 2 to give a quantitative description of the problem[19]. ρ is the charge density of the dielectric on the bottom electrode, and is a time-dependent variable determined by applied voltage, dielectric material properties and environmental param-eters[2023]. Applying Gauss’s Law for a Gaussian surface that surrounds the bottom sheet charge,

Figure  2.  A capacitor dielectric with dielectric sheet charges density ρ.
ε0(εrE2E1)=ρ, (7)

where εr is the relative permittivity of the dielectric, E1 is the electric field in the gap between the top electrode and bottom dielectric, E2 is the electric field in the dielectric between ρ and the bottom plate. Summing the electric fields according to Faraday’s law,

(gd)E1+dE2=V, (8)

where g is the equilibrium gap, and d is the thickness of the dielectric layer. The effective potential drop Veff across the air gap is

Veff=(gd)E1. (9)
Veff=(Vdρε0εr)/(1+dg). (10)

The portion of the effective voltage due to trapped surface charge is called the “built-in” voltage[24],

Vbi=VVeffdρε0εr=dQε0εrA, (11)

where Q is the total charges in the dielectric layer and A is the area of the electrode.

Three models of the dielectric charge dynamics were described in Ref. [25]. However, the dielectric charges are all time-dependent variables. In the most general case, we use the exponential dynamics model to describe the dielectric charge. The dynamics of the charge resembles an exponential form

Q(t)=Qmax(1et/τ). (12)

So

Vbi=dρε0εr=dε0εrA×(Qmax(1et/τ)), (13)
Vs=dε0εrA×Qmax, (14)

where Vs is the saturation voltage eventually reached by dielectric charges and time constant τ represents the characteristic time scale of the process.

We could obtain that the effective voltage is a function of ρ, and is not the same with the applied DC voltage at most times. For the devices that are actuated by the electrostatic force, the bias voltage will soften the resonant element and generate a negative stiffness effect[12, 13]. When the electrostatic stiffness co-exists with the mechanical stiffness, the resonant frequency of the sense mode can be expressed as

ω=k+Δkm=kxzy3ε0(V+Vbi)2m. (15)
ω(t)=k+Δkm=kxzy3ε0(V+Vs(1et/τ))2m. (16)

It suggests that the resonant frequency is related to the effective voltage. So the parasitic charge in the dielectric layer would lead to the frequency drift of the gyroscopes and affect the output stability.

Take Eq. (16) into Eq. (5) and make the necessary omission in the calculation, the output of the gyroscope is

uZRO(t)=G|kxzy3ε0(V+Vs(1et/τ))2mωd2|, (17)

where G is a gain constant.

In this section, we discuss the analytical and experimental results of the MEMS gyroscopes working at different bias conditions.

The gyroscope in the experiment is based on the well proven Sensonor ButterflyGyroTM structure[26] and encapsulated with Pyrex glass which act as the dielectric material in this case. The asymmetric driving beams of this structure lead to an obvious mechanical properties difference between the drive and sense mode. The parameters of the gyroscope in the experiment and some constants used in the simulation are shown below in Table 1.

Table  1.  The parameters of the gyroscope and some constants used in simulation.
Parameter Symbol Value Unit
Drive-mode frequency wx 13.467 kHz
Drive-mode stiffness kx 50 000 N/m
Sense-mode stiffness ky 870 N/m
Sense-mode mass my 1.2 × 10−7 kg
Gap g 2 × 10−6 m
Area A 1.4 × 10−6 m2
Air permittivity ε0 8.854 × 10−12 N/m
Relative permittivity εr 3.9
Gain constant (6 V) G 3.2 × 108 V·kHz2
Gain constant (5 V) G 2.8 × 108 V·kHz2
DownLoad: CSV  | Show Table

Fig. 3 shows both the drive and sense resonant frequency with different DC bias voltage of the MEMS gyroscopes. According to the observation data, the resonant frequency of the drive mode keeps constant. This is owing to the fact that the mechanical stiffness of the drive mode is relatively high so that the Δk is omitted. Yet the mechanical stiffness of the sense mode is several magnitudes lower than the drive mode and the Δk is unneglectable. So there is a frequency drift of the sense mode.

The drifting tendency is related to the τ and Vs; we give the simulation results in Fig. 4. The time constant τ represents the characteristic time scale of the drifting process and does not show a significant difference with different bias voltage. They both turn out to be about 1300 s. Vs is the saturation voltage eventually reached by dielectric charges which has a positive correlation with the bias voltage. The value of Vs is 0.052 V with 6 V bias voltage while it is 0.032 V with 5 V bias voltage.

Figure  4.  (Color online) (a) Sense mode frequency drifting with different τ and 6 V DC bias voltage. (b) Sense mode frequency drifting with different Vs and 6 V DC bias voltage. (c) Sense mode frequency drifting with different τ and 5 V DC bias voltage. (d) Sense mode frequency drifting with different Vs and 5 V DC bias voltage.

Due to the frequency drift, the ZRO of the gyroscope is shown in Fig. 5. Fig. 5(a) is the output applied with 6 V DC voltage, while Fig. 5(b) is with 5 V DC voltage. We can see that the output presents an obvious tendency, and takes about 2000 s to reach a stable value. Fig. 5(c) shows the output tendency during a DC voltage changing process. Initial 7000 s shows the output with 6 V DC voltage and it corresponds with Fig. 5(a). Then the voltage reduced to 5 V during 7000–13 000 s, the output voltage changed to −1.25 V, which is the same as the stable state in Fig. 5(b). Between 13 000–18 000 s the voltage changed to 6 V again and the output turned out to be −0.86 V, which is equal to the first period. Fig. 5(c) shows the simulation and test results of ZRO with 6 and 5 V DC bias voltage. The test result matches the simulation perfectly when the bias voltage is 6 V while there is an error between them when the bias voltage is 5 V. As we can see in Figs. 3(a) and 3(c), the mismatch between drive mode and sense mode is clearer with 6 V bias voltage, so the drift of sense mode has less impact on the ZRO. However, the mismatch is less clear when the bias voltage is 5 V and the ZRO is more sensitive to the frequency drift, and what is more, G is no longer a constant anymore, which contributes to the error between the test and simulation results.

Figure  5.  (Color online) (a) The ZRO of the gyroscope with 6 and 5 V DC bias voltage. (b) The ZRO of the gyroscope with 6, 5, and 6 V DC bias voltage. (c) The simulation and test results of ZRO with 6 and 5 V DC bias voltage.
Figure  3.  (Color online) (a) The drive and sense mode resonant frequency of the MEMS gyroscopes with 6 V DC bias voltage. (b) The sense mode resonant frequency drifting of the MEMS gyroscopes with 6 V DC bias voltage. (c) The drive and sense mode resonant frequency of the MEMS gyroscopes with 5 V DC bias voltage. (d) The sense mode resonant frequency drifting of the MEMS gyroscopes with 5 V DC bias voltage.

According to the previous discussion in Section 2, it is the DC voltage rather than AC voltage that makes the dielectric charge undergo a redistribution process. To verify this phenomenon and exclude the thermal effect, we use the testing scheme in Ref. [27] for reference. As in Fig. 6, we make the gyroscope only applied with AC ± 6 V or DC 6 V bias voltage but not actuated, and write down the outputs every twenty minutes. The results are shown in Fig. 7.

Figure  6.  Measurement-stressing scheme used for testing.
Figure  7.  (Color online) Output of the gyroscope for AC stressing and DC stressing.

As we can see in Fig. 7, the output of the gyroscope with DC stressing has a similar trend with Fig. 5(a), while the output with AC stressing is basically stable, verifying that the DC voltage is the cause of the dielectric charge accumulating and frequency drift.

According to the analysis above, the drift induced by charging only occurs when both dielectric layers and DC bias exist at the same time, therefore, it can be overcome by eliminating one or both of their existences.

The dielectric layers in MEMS devices could be divided into two kinds. They are created either by natural chemical reaction or by artificial means. For the former, it is difficult to totally prevent the materials from such oxidation, so what we could do is to control the processing environment to the utmost extent. For the latter, we could improve the dielectric quality by optimizing the deposition process to reduce the defects in the dielectric layers[28, 29] or by using a dielectric which has higher dielectric constants and lower leakage current density.

On the other hand, the DC bias is another cause of drifting, so a commonly adopted measure is to replace the DC bias by AC bias. However, the change of bias would lead to the failure of the origin actuation mode, so we have to redesign a feasible method. Other approaches include reducing the actuation voltage, applying the non-electrostatic actuation and so on.

Output voltage drift was observed in MEMS gyroscopes. We studied the variation of the parasitic charge and analyzed the effect of the parasitic charge on the output stability. Due to the DC voltage required for the electrostatic actuation, the charges in dielectric will undergo a process of redistribution to induce a residual voltage. The voltage is a time-dependent variable so that it affects the resonant frequency of the gyroscopes, furthermore, the output of the gyroscopes. According to the simulation and experimental results, the saturation voltage eventually reached by dielectric charges has a positive correlation with the bias voltage. The time constant τ representing the characteristic time scale of the drifting process does not show significant difference with different bias voltage. It takes about 2000 s for the output voltage to reach a stable value.



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Fig. 1.  (Color online) (a) Schematic illustration of the electromagnetic spectrum ranging from visible to infrared regions. (b) Spectral response ranges of commonly used materials with different dimensions for infrared photodetection.

Fig. 2.  (Color online) (a) Schematic illustration of a photoconductor photodetector array. (b) Schematic illustration of a photodiode photodetector array. (c) Schematic illustration of a phototransistor photodetector array.

Fig. 3.  (Color online) (a) Schematic illustration of the fabrication process for a TiN/GeSn heterojunction photodetector, and (b) corresponding optical photograph[45]. (c) Schematic illustration of epitaxial AlAs and InxAl1−xAs arrays directly grown on a GaAs substrate, and (d) corresponding SEM cross-sectional image[46].

Fig. 4.  (Color online) (a) Schematic illustration of an infrared photodetector based on UCNPs and BHJ, with corresponding mechanism diagram. (b) Normalized absorbance spectra of DPPTT−Tin solution, resulting film, and UCNP upconversion fluorescence spectrum[57]. (c) Chemical structures of two narrow bandgap semiconductors, PBTT and PBTB. (d) and (e) Absorption spectra of PBTT and PBTB in solution and as fabricated films, respectively[58].

Fig. 5.  (Color online) (a) Schematic illustration of various 2D TMDs and end-functionalized polymers. (b) Absorbance spectra for a range of two-dimensional materials. (c) Schematic and optical photographs of a photodetector array composed of MoSe2 films exfoliated by PS−NH2, scale bars: (ⅰ) 6 mm; (ⅱ) 500 mm. (d) Schematic illustration of a flexible infrared detector using MoSe2−PS−NH2 composite films and its film morphologies, scale bars: (ⅲ and ⅳ) 500 nm. (e) Schematic illustration of a flexible infrared detector using MoSe2/MoS2−PS−NH2 composite films and its EDS mappings, the scale bar, 2 mm[84].

Fig. 6.  (Color online) (a) Schematic illustration of the PbS quantum dot photodiode structure accompanied by its cross-sectional SEM image, and (b) the corresponding energy level diagram. (c) Schematic of the integration of PbS quantum dots with polyimide[88]. (d) Absorption spectra of quantum dot solutions with and without polyimide after 24-h storage. The inset is the optical photograph of quantum dot solutions; the left without PI, and the right with PI[89]. (e) Schematic illustration of a device utilizing CQDs for the infrared-sensitive layer. (f) Schematic of mask imaging under infrared illumination[90].

Fig. 7.  (Color online) (a) Schematic illustration of one-dimensional polymer nanowires with donor−acceptor (D−A) core-shell heterojunction structure[92]. (b) Schematic illustration of a Ga−In2O3 nanowire phototransistor. (c) Performance comparison of Ilight/Idark ratios with similar devices[93]. (d) Morphologies of Te nanomeshes directly grown on various substrates[94].

Fig. 8.  (Color online) (a) Schematic illustration of the fabrication process for a flexible InAs photodetector, employing molecular beam epitaxy and epitaxial lift−off techniques. (b) Schematic diagram of the device with vertical stacking structure[47].

Fig. 9.  (Color online) (a) Schematic illustration of the physical vapor deposition setup for depositing Sb2Te3. (b) Film morphology and composition after varying deposition times[103]. (c) SEM image of directly epitaxial Sb2Se3 films grown on mica substrates and (d) corresponding XRD spectra. (e) IV curve comparisons for photodetectors fabricated from epitaxial and non-epitaxial Sb2Se3 films[44].

Fig. 10.  (Color online) (a) Schematic illustration of the fabrication process for flexible electronic devices using metal−organic chemical vapor deposition. (b) Optical photograph and structural diagram of large-area MoS2 prepared on a flexible parylene-C substrate[109].

Fig. 11.  (Color online) (a) Process diagram for the fabrication of PbS and ZnO quantum dot heterostructure via spin-coating and (b) schematic illustration of the completed device. (c) Absorption spectra of PbS, ZnO, and PbS/ZnO films. (d) IV curves of the PbS/ZnO quantum dot heterojunction photodetector under various light intensities[112]. (e) Process diagram for fabricating flexible NIR photodetectors using all-template printing. (f) IV curves at different radii of curvature[114].

Fig. 12.  (Color online) (a) Chemical structure diagrams of YZ and YZ1 and (b) PCE-10. (c) Absorption spectra of YZ, YZ1, and PCE-10 films. (d) Energy level and structural diagrams of the corresponding photodiode[118]. (e) Mu−tau product for spray-coated FAPbI3 and PEA2FA3Pb4I13 films. (f) Charge distribution across the PEA2FA3Pb4I13 film at different wavelengths, modeled from diffusion lengths and absorption spectra. (g) Normalized external quantum efficiency responses of perovskite photodetectors with varying halide compositions[119].

Fig. 13.  (Color online) (a) Schematic illustration of the device structure and working mechanism for a SWCNT/graphene and MoS2 dual heterojunction and (b) corresponding optical photograph. (c) Schematic of the fabrication process for the SWCNT/graphene and MoS2 dual heterojunction photodetector[125].

Fig. 14.  (Color online) Schematic illustrations of the device on a stretchable substrate in (a) bent and (b) stretched configurations[130]. (c) Schematic of the electrode fabrication process and flexible photodetector using direct writing with a pencil and Chinese brush[135].

Fig. 15.  (Color online) Schematic illustration of a 3D integration strategy for (a) integrated sensor system[156] and (b) multilayer two-dimensional material integration[157]. (c) Schematic illustration of a multifunctional integration strategy for full-color recognition[162].

Fig. 16.  (Color online) (a) Schematic illustration of a flexible photodetector for detecting PPG signals on the wrist[167]. (b) Schematic illustration of a NIR photodetector designed for remote health monitoring. (c) Schematic illustration of a photodetector array for NIR biomimetic curved imaging[93].

Fig. 17.  (Color online) Schematic illustrations of curved photodetectors fabricated using various strategies (a) ultrathin substrate design[150], (b) origami/kirigami design, scale bar: 1 mm[175], (c) island−bridge structure[176], (d) fractal web structure[177], and (e) in situ growth of nanowires[178].

Table 1.   Summary of the characteristics of various flexible infrared photodetectors.

Materials Materials
type
Configurations Wavelength range (nm) Operating temperature Detectivity (Jones) Responsivity Refs.
TiN/GeSn Bulk Photodiode 1000−2530 / 8 × 108 218 mA/W [45]
Sb0.405Te0.595 Bulk Photoconductor 405−4500 27−127 °C 6.435 × 108 588 A/W [103]
Sb Bulk Photoconductor 405−1064 Room temperature / 21.8 µA/W [43]
GaAs Bulk Photoconductor 800−1700 20−55 °C / ~1 A/W [42]
Sb2Se3 Bulk Photoconductor 525−940 Room temperature 8.58 × 1010 155 mA/W [44]
Te Bulk Photoconductor 10 800 Room temperature 8.63 × 107 60.03 mA/W [190]
SnS2 Bulk Photoconductor 400−980 / / 44.5 mA/W [101]
D18:BTP-4F Organic Photodiode 400−900 / 6.45 × 1012 206 mA/W [191]
YZ&TZ1 Organic Photodiode 300−1050 / 9.24 × 1013 0.27 A/W [118]
Graphene/C60 Organic Photoconductor 360−808 Room temperature / / [192]
SWCNT/GdIG/Gr/
GdIG/MoS2
Organic Photoconductor 400−1500 Room temperature 4.504 × 1012 109.311 A/W [125]
Cs0.05MA0.45FA0.5
Sn0.5Pb0.5I3
Organic Photodiode 350−1000 / 1.6 × 109 0.2 A/W [193]
SnS1.26Se0.76 2D Photoconductor 375−808 Room temperature / 120 mA/W [74]
Te 2D Photoconductor 500−1342 / 2.489 × 10–4 3.325 A/W [141]
MoTe2 2D Photoconductor 380−1100 / / 10.4 µA/W [194]
SnTe 2D Photoconductor 980 Room temperature 3.89 × 108 698 mA/W [75]
CNTs/MoS2 2D Photoconductor 400−1500 Room temperature 4.504 × 1012 109.311 A/W [125]
PdSe2 2D Photoconductor 365−2200 / / 37.6 mA/W [195]
a-SiGe 1D Photodiode 320−1000 / / 140 mA/W [196]
Bi2Se2S 1D Phototransistor 915−1550 Room temperature 3.1 × 1010 2.9 A/W [93]
SnSnS3 1D Photoconductor 250−1064 / 3.0 × 1010 154.3 A/W [197]
Te 1D Phototransistor 520−1550 Room temperature / 23.3 A/W [94]
NbS3 1D Photoconductor 375−118 800 / 17.6 × 105 6.90 V/W [198]
PbS/CdS 0D Photodiode 1360−1400 Room temperature 4.0 × 1012 612 A/W [199]
PbS 0D Photoconductor 1000 / 2.02 × 109 2.1 A/W [200]
PbS 0D Photodiode 1300 / ~1013 / [89]
CsPbBr3/PbSe 0D Photoconductor 365−1854 / ~1012 / [111]
PbS 0D Photodiode 390−1100 / 1.01 × 1012 0.38 A/W [88]
PbS 0D Photodiode 400−1600 / 6.4 × 1012 >60 A/W [90]
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    Yegang Liang, Wenhao Ran, Dan Kuang, Zhuoran Wang. Design strategies and insights of flexible infrared optoelectronic sensors[J]. Journal of Semiconductors, 2025, 46(1): 011602. doi: 10.1088/1674-4926/24080044
    Y G Liang, W H Ran, D Kuang, and Z R Wang, Design strategies and insights of flexible infrared optoelectronic sensors[J]. J. Semicond., 2025, 46(1), 011602 doi: 10.1088/1674-4926/24080044
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    Received: 28 July 2024 Revised: 20 September 2024 Online: Accepted Manuscript: 10 October 2024Uncorrected proof: 03 December 2024Published: 15 January 2025

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      Yegang Liang, Wenhao Ran, Dan Kuang, Zhuoran Wang. Design strategies and insights of flexible infrared optoelectronic sensors[J]. Journal of Semiconductors, 2025, 46(1): 011602. doi: 10.1088/1674-4926/24080044 ****Y G Liang, W H Ran, D Kuang, and Z R Wang, Design strategies and insights of flexible infrared optoelectronic sensors[J]. J. Semicond., 2025, 46(1), 011602 doi: 10.1088/1674-4926/24080044
      Citation:
      Yegang Liang, Wenhao Ran, Dan Kuang, Zhuoran Wang. Design strategies and insights of flexible infrared optoelectronic sensors[J]. Journal of Semiconductors, 2025, 46(1): 011602. doi: 10.1088/1674-4926/24080044 ****
      Y G Liang, W H Ran, D Kuang, and Z R Wang, Design strategies and insights of flexible infrared optoelectronic sensors[J]. J. Semicond., 2025, 46(1), 011602 doi: 10.1088/1674-4926/24080044

      Design strategies and insights of flexible infrared optoelectronic sensors

      DOI: 10.1088/1674-4926/24080044
      CSTR: 32376.14.1674-4926.24080044
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      • Yegang Liang received his bachelor's degree in 2020 and his master's degree in 2023, both from Guangxi University. He is currently a doctoral student at Beijing Institute of Technology, focusing on the research of flexible and curved infrared sensors
      • Wenhao Ran received his PhD in the Institute of Semiconductors, Chinese Academy of Sciences in 2022. He is currently a postdoctoral researcher at the School of Integrated Circuits and Electronics, Beijing Institute of Technology, Beijing. His current research focuses on flexible biomimic vision system with in-memory sensing and computing
      • Dan Kuang received her doctoral degree from Beijing institute of technology, China, in 2023. She is currently an experimentalist with school of integrated circuits and electronics, Beijing institute of technology, China. Her current research focuses on semiconductor nanomaterials and flexible devices
      • Zhuoran Wang received his PhD in the Mining and Materials Engineering from McGill University, QC, Canada in 2017. In 2019 he joined the Institute of Photonic Sciences (ICFO), Barcelona, as a postdoctoral/Marie-Curie research fellow. He is currently a professor at the School of Integrated Circuits and Electronics, Beijing Institute of Technology, Beijing. His current research focuses on flexible optoelectronic sensors for biomimic vision
      • Corresponding author: Zhuoran.wang@bit.edu.cn
      • Received Date: 2024-07-28
      • Revised Date: 2024-09-20
      • Available Online: 2024-10-10

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