Random lasing in liquid crystals: advances, challenges, and future directions

Abstract

Random lasing in liquid crystals is an emerging field that combines the unique optical properties of liquid crystals with the fascinating behaviour of random lasers. This review provides a comprehensive analysis of the basic principles of random lasing, highlights the unique properties of liquid crystals, and examines strategies for optimizing laser performance in this context. Furthermore, we discuss the promising applications of liquid crystal-based random lasers across diverse fields, including telecommunications, display technologies, and sensing. Despite significant progress, challenges persist in enhancing the reliability and operational stability of these systems. To address these issues, we outline potential research directions, such as integrating random lasers into new technologies and developing novel liquid crystal materials. These initiatives have the potential to drive breakthrough innovations in photonics and related fields.

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Introduction

In 1917, Albert Einstein proposed the concept of light amplification through stimulated emission of radiation (LASER), laying the foundation for developing this remarkable technology.¹ By shifting the focus from microwaves to visible wavelengths, the laser emerged as a regulated light source capable of producing coherent beams akin to microwave oscillators. Building on Einstein's work, laser research accelerated during the mid-20th century, spurred by advancements in radio and microwave technologies. In the early 1960s, key contributions from scientists like R. V. Ambartsumyan were pivotal in creating both LASERs and MASERs, including methods for achieving oscillation in pumped gain media without needing an enclosed cavity. This concept led to the development of “non-resonant feedback lasers” in 1966.² They demonstrated how to keep oscillation in a pumped gain medium without forming an enclosed cavity with two mirrors.³

This new approach evolved further with the introduction of random lasers (RLs) in 1970, where V. S. Letokhov and colleagues explored the phenomenon of light generation through scattering media with negative resonance absorption.⁴ They laid the theoretical groundwork for random lasing by interpreting non-resonant feedback regarding optical modes within an open cavity.⁵ Following the initial years of research, random lasers remained relatively dormant in the scientific community until a notable development in 1986 when Markushev and colleagues published their work on a powder laser.⁶ Subsequent work, such as the demonstration by Lawandy and colleagues in 1994, showed that RLs could be realized in intense scattering media, particularly in systems involving colloidal suspensions of organic dyes and nano meter-sized rutile (TiO₂) nanoparticles.⁷ This experiment marked a major validation of random lasing principles and formally introduced the term “random laser,” leading to new applications in sensing, communications, and photonics.^8,9Fig. 1 illustrates random lasers’ development progress since their discovery.

Fig. 1 Timeline for the development of random lasers.

The term “random media” refers to a disordered medium where photons undergo multiple scatterings, resulting in an extended dwell time and improved effectiveness of light amplification. In conventional lasers, feedback is provided through a resonant cavity, typically consisting of two mirrors, which direct the light back into the gain medium (Fig. 2a). In contrast, random lasers rely on scattering within the disordered medium for feedback, eliminating the need for a closed cavity (Fig. 2b).¹⁰ Unlike traditional lasers, random lasers in liquid crystals leverage the anisotropic and reconfigurable nature of liquid crystals, enabling unique tunability through external fields such as electric and magnetic fields. This tunability enables real-time adjustments of laser characteristics, including wavelength and threshold, which is impossible with traditional cavity-based lasers. In addition, random lasers possess dynamic and spectral properties that make them effective in both stable and random environments.¹¹ Liquid crystals, widely used in random lasing research, offer significant advantages due to their optical and physical properties. Their strong scattering and anisotropy give rise to phenomena such as diffraction, optical rotation, Bragg reflection, and magneto-optic effects.¹²

Fig. 2 (a) Schematic depicts a conventional laser with two mirrors and an active medium; and (b) random laser having multiple scattering. Reproduced with the permission from ref. 10. Copyright 2022 Elsevier Ltd.

Liquid crystals are a unique form of matter that combines the properties of both crystalline solids and liquids (Fig. 3a). Liquid crystals can be categorized into two main types: thermotropic and lyotropic. The thermotropic liquid crystals are further divided into three phases based on the arrangement of molecules: nematic, cholesteric, and smectic phases (Fig. 3b).¹³

Fig. 3 (a) The arrangement of rod-shaped molecules in both crystalline and liquid states; and (b) the molecular organization in various liquid crystal (LC) phases.

Liquid crystals can undergo phase transitions due to their unique fluidity and long-range orientational order. Their characteristics can be easily adjusted at different temperatures and magnetic and electric fields, making them suitable as disorder media to control RLs. In dye-doped liquid crystal systems, the guest–host effect is crucial in which dye molecules (guests) interact with the liquid crystal matrix (hosts). This interaction improves optical properties such as laser efficiency and tunability, making liquid crystals an ideal gain medium for random lasers. The idea of liquid crystal lasing was introduced in 1973 by Goldberg and Schnur,¹⁴ and experimental proof was provided 25 years later by Kopp et al. Since then, liquid crystals have been extensively researched to study light amplification phenomena.¹⁵ Liquid crystals have emerged as an intriguing material for developing and utilizing new laser light sources due to their ability to trap and slow down light with frequencies near the band gap.^16,17 Random lasing with liquid crystals creates new opportunities for sensing, communication, and display technologies.

Building on the significant contributions of previous studies such as nanophotonic,¹⁸ which explored the fundamental principles and established applications of random lasing in liquid crystals, these works primarily focus on static systems and conventional methodologies. Similarly, the study by Qu et al.¹³ delves into the principles of random lasing in liquid crystals, emphasizing wavelength tuning, threshold control, and polarization properties. In contrast, this paper stands out by investigating multi-field tunability, including electrical, magnetic, and thermal effects, which are essential for advancing practical applications. Additionally, this review highlights the growing influence of machine learning in optimizing laser thresholds and emission characteristics, an area that has often been overlooked. It also critically addresses the challenges associated with these systems, offering perspectives on future developments, and aims to guide further research and innovation in liquid crystal-based laser systems. This work distinguishes itself from previous reviews by addressing these gaps and presenting novel insights and strategies to propel the field forward.

Basic principles of random lasers

The mode structures of lasers are crucial. In conventional lasers, modes are controlled by the cavity (Fig. 4a). Random lasing has a distinct mode and is generated in systems with weak and strong scattering (Fig. 4b). Before leaving the gain media, the spontaneously generated photons are subjected to repeated scattering. More photons are produced through stimulated emission while the photons move through the gain media. The spatial resonance of photons is lost due to incoherent feedback, as scattering only returns a portion of the photons to the gain media. Scattering can form a closed loop in disordered nanostructures, producing coherent feedback. As illustrated in Fig. 4c, its primary attribute is the spectrum emission's laser spikes, the key difference between a random laser with coherent input and another with incoherent feedback.¹⁹

Fig. 4 (a) A conventional laser cavity; (b) random lasing cavity demonstrating the incoherent and coherent feedback; (c) spectral outputs of conventional laser and random laser. Reproduced with permission from ref. 13. Copyright 2015 Elsevier Ltd.

Fundamentals of random lasers

The following is a summary of the fundamentals of random lasers:

Disordered media

Disorder or randomness characterizes the medium where random lasing takes place. This could be a liquid, a powder, or other material with an unorganized structure. Multiple light-scattering channels are introduced within the medium by the disorder.²⁰

Multiple scattering

Multiple light scattering is present in almost all optical materials that appear foggy, including powders, white paint, mists, and even human tissues. Before escaping from the materials, light beams seem randomly scattered millions of times after entering the opaque materials in multiple scattering.²⁰ Light waves in cluttered optical structures, also referred to as random lasers, are both amplified and multiply scattered.²¹ Since light waves in these opaque materials are scattered several times in unpredictable patterns before exiting the substance, they travel randomly inside of them, giving the illusion of being white. Without sacrificing the coherence of light, these many light scattering processes produce the bewildering impedance design known as speckle.

Gain media

Aside from multiple light scattering, optical gain is another component required for the random lasing system. It becomes active when a high-energy pump source stimulates the gain material. When light travels through an amplifying or gain substance, it may interact. When light is sufficiently magnified before it exits, lasing activity occurs.

The lasing emission variables, including output intensity, wavelength, and operation type, are determined by the gain medium, which adds energy to the amplified light. Each of the many gain media utilized in laser technology has a distinctive gain profile. The appropriate gain media must be chosen for laser equipment design and applications based on key gain characteristics such as tunability, pumping ranges, efficiency, and capability.¹⁸ The most popular are (i) band-gap semiconductors like GaAs, In GaAs, and GaN₃O₉,²² (ii) laser crystals and glasses,²³ (iii) crystals that have been ion-doped, such as Al₂O₃ with Cr³⁺ ions,²⁴ (iv) dye lasers,²⁵ and (v) gas lasers.²⁶ Gain medium needs to have a few essential qualities such as high transparency, chemical durability, high optical damage threshold, high energy pulse amplification, and ultra-short pulse generation to amplify light.²⁴

When there is enough scattering and amplified scattered light to compensate for the loss as it exits the gain medium, random lasing performs best.²⁷ The emitted photons move and get more intense inside the active gain zone till they finally exit the area. Therefore, eqn (1) describes the required condition of random lasing to counter the loss before photons leave the medium and sufficiently intensify the light.²⁸

l_s ≥ l_g (1)

Table 1 demonstrates the primary random lasing operating concept concerning gain medium, scattering and operational principles.

Table 1 The primary RL operating concept concerning gain media scattering and operational principle

Gain medium	Scatterer	Operational principle	Threshold	Ref.
Laser dye	Nanoparticles	Irregular dye emission is reflected by disorganized polymeric nanoparticles.	0.013 MW cm^−2	29
	Ay–Ag nanowire		0.029 MW cm^−2
Rare earth ions	Rayleigh scattering, FBGs (fiber brag gratings)	Excitation of rare earth excited ions and their reflection back through randomly inserted FBGs	18 MW cm^−2	30
Dye doped LCs	Liquid crystal	The director variations of the dye-doped LC feedback the stimulated emission from the LC.	0.2 mJ cm^−2	31
Perovskite QDs	Vertical-graphene nanowalls	Minimal threshold energy of density coherent emission	10 nJ cm^−2	32
Rhodanium 6G	Fat, muscle, and nerve	The concept of distinguishing nerve from other tissue components.	The threshold varies across different specimens.	33
Pyrromethene 597	Ferromagnetic nematic liquid crystal	Coherent random lasing emission	—	31
Semiconductor optical amplifier	Rayleigh scattering	A carefully engraved random FBG feeds back the enhanced emission from an SOA.	—	34
Colloidal QDs	Silicon nanowire array	Transformation of RL from incoherent to coherent.	The resistance of silicon wafers and the dimension of silicon nanowires affect the threshold.	35

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Characteristics of random lasers

Random laser emission. Coherent and incoherent emissions are the two unique spectral characteristics of random lasers. Coherent/resonant emission features numerous narrow peaks with a sub-nanometre linewidth, distributed randomly in frequency, while incoherent/non-resonant emission has a single-peak spectrum of a few nanometres.²⁸

When several narrow emission peaks emerge, a coherent random laser produces lasing.^36,37 These narrow peaks, often called random laser peaks, arise from coherent feedback due to closed photon scattering paths within the disordered medium. The presence of such peaks is a hallmark of random laser systems and distinguishes them from incoherent laser phenomena.

Similarities exist between random and regular lasers, such as the ability to produce well-defined colours and pulse-like outputs due to extremely narrow emission spectra.³⁸ The gain medium generates light when a photon passes through it and stimulates a second photon. The gain length surpasses the mean path length of photons within the gain medium at frequencies near the maximum of the gain spectrum.³⁹ As a result, the likelihood that a photon will produce a second photon will get closer to one, indicating the sudden increase in emission intensity. A narrow emission peak is produced by this abrupt increase in emission intensity at the gain spectrum's maximum.⁴⁰Fig. 5a shows the emission linewidths of Rh6G/silver random lasers with increased pump energy density.

Fig. 5 (a) Shows that as the pump energy density increases, the emission linewidths of Rh6G/silver random lasers gradually narrow and (b) the onset of lasing occurs when a clear surge is observed in the transition pattern. (c) and (d) The interference patterns and intensity profile are key indicators for evaluating both spatial and temporal coherence. Reproduced with permission from ref. 21. Copyright 2020 AIP Publishing.

Multiple emission peaks with sub-nano meter linewidths can appear over a broad fluorescence background as the scattering increases.⁴¹ In the weak scattering regime, random variations in the refractive index can lead to waveguiding and the formation of resonant modes, resulting in the appearance of multiple emission peaks with large transport mean free paths.²⁷ The appearance of spiky emission depends on the resolution of the detection system, the properties of the nanostructures, and the duration of the pump pulse.^20,39 Additionally, the emission wavelength in a random laser can be adjusted and tuned⁴² by altering the particle or structure size and absorption, which influence the gain curve and mode selection.⁴³ Moreover, the emission wavelength can also be controlled by modifying parameters like temperature, electric field, and pump beam distribution. In a random laser using liquid crystals, applying a small voltage to the sample can alter the refractive index of the liquid crystal, allowing the emission wavelength to be shifted and tuned.⁴⁴ The parameters that determine RL emissions that have been studied differ throughout the authors.⁴⁵ The most general influencing elements of the RL emission properties are outlined in Table 2, along with examples for each.

Table 2 Influencing elements of random lasing emission properties

RL emission properties	Contributing elements	Experimental factors	Explanation	Ref.
	Illumination	Pump spatial and temporal profile. (pluse duration)	The spatial and temporal profile of the pump light affects energy distribution and lasing efficiency in the medium	46 and 47
	Pumping conditions	Intensity and area	The intensity of the pump source influences the onset of lasing and the overall efficiency of the random laser.	48
Tunability	External fields	Angle and intensity	The application of external electric or magnetic fields can change the orientation of liquid crystals or affect the gain medium's properties, providing a means of tuning the random laser emission.	49
Lasing threshold	Scatterers	Size and concentration	The scattering centers within the gain medium, which can be particles or defects, play a key role in the random lasing process.	50 and 51
Coherence	Geometry and morphology	Size and shape	The size and distribution of scattering centers in the gain medium significantly influence the scattering mean free path and random lasing behavior.	52
Polarization	Dye	Concentration	The properties of the laser gain medium, such as the type of laser dye used, its concentration, and absorption/emission characteristics, strongly influence random laser emission.	53 and 54
Scattering	Solvent	Refractive index difference	The intrinsic properties of the host material, such as refractive index, also important in determining the emission properties of random lasers.	55 and 56

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Lasing threshold

The lasing threshold in random lasers is a crucial factor influenced by the scattering mean free path of photons and the light-gathering efficiency of the gain media.²⁷ The pump energy density impacts the lasing threshold, located at the start of a nonlinear spike in emission intensity. The lasing threshold of a common laser is determined by the start of the output power's nonlinear increment based on the input power.²⁸ A random laser encounters a lasing threshold during a pump's shift, determined by the pump energy density, and occurs at the beginning of a nonlinear increase in emission intensity. Some variables that can affect the performance of the lasing threshold are the amount of the scatters, their refractive index for the adjacent media, the diameter of the stimulation spot, energy transfer, and dye concentration.⁵⁷ The lasing threshold of a random laser is dependent on the dye concentration and particle size in a medium.^8,58

An experiment by Burin et al. from 2003 showed how the dye concentration, the pump area, and the light transit length influence the lasing threshold. The experiment revealed that the lasing threshold intensity decreases with light transport length and beam diameter saturation at 200 μm or 1 mm and inversely decreases with increasing dye concentration.³⁹ When one or both dye and particle concentrations increase, the lasing threshold falls.^1,40

However, Cao et al.'s research⁵⁸ demonstrated that the lasing threshold can be lowered if the photons’ scattering mean free path in zinc oxide is shorter than the stimulated wavelength. Increases in the number of scatterers 8, higher available gains,⁵⁷ or greater refractive index contrast between the scatterers and the surrounding medium can also reduce the lasing threshold.⁵⁵Fig. 5b demonstrates that the threshold for laser emission is attained when a sudden shift in the transition pattern occurs.

Coherence

The primary characteristic that sets a laser apart from other light sources is the coherence of the radiation.³⁴ The capacity of light to produce interference effects is known as optical coherence. Coherent light is produced when the electric field values at different places or times have a constant phase relationship. The partially coherent light originates when there is a partial relationship between phase values.⁵⁹ Random and regular lasers have spatial and temporal coherence, allowing the beam to focus on a small area and producing a narrow laser spectrum.³⁴ A coherent source is characterized by a Bose–Einstein photon distribution, in contrast to the Poisson photon distribution typically associated with incoherent sources.³⁴ Cao et al. studied the photon distribution's transition from Bose–Einstein to Poisson in a coherent random laser upon reaching the lasing threshold.⁶⁰ The experiment was repeated using an incoherent Rhodamine 6G-TiO₂ system, demonstrating that random lasers can exhibit partial coherence by combining Poisson and Bose–Einstein distributions based on photon statistics.³⁴

Additional studies on disordered nanostructures were conducted to explore the coherent characteristics of random lasers, incorporating both strong and weak scattering. The tests demonstrated that temporal coherence can be measured using a Twyman–Green interferometer and a Michelson interferometer setup. In contrast, spatial coherence can be measured using Young's two-slit interferometric approach.⁶¹ WZW Ismail et al.³⁸ also investigated temporal and spatial characteristics of random laser coherence. Fig. 5c and d display the interference fringes and intensity distributions above the lasing threshold.

The underlying connection between liquid crystals and random lasers

Different “textures” and optical qualities arise from the direction of the LC molecules’ optical axis, which changes in response to external factors like temperature and electric field. At various temperatures, phase changes can occur in the LC. The distribution difference in refractive index is caused by a change in the alignment orientation of the LC molecules. The direction of alignment with the LC molecules shifts when the LC is subjected to an electric field. These qualities allow LCs to be employed as disorderly media to regulate random lasers.¹³

LC is the disordered scattering medium in liquid crystal random lasers and changes in the LC phase or LC molecule arrangement can alter its anisotropic distribution. This makes adjusting the RL radiation's threshold, polarization, and lasing wavelength possible.

Manipulation of random lasing wavelength through liquid crystals

Using LC's ideal responsive characteristics as a medium of dispersion allows for the adjustment of both the system's degree of disorder and the dye molecules’ orientation. As a result, the LCRL application range can be greatly increased by controlling the LCRL optical properties.⁶¹ By adjusting the cholesteric LCs’ reflection band inside the stimulation fluorescence spectral range, cholesteric LC lasers’ tunable lasing wavelength is suggested. There are several techniques to attain tunable LCRL, such as adjusting the temperature,⁶² voltage,⁴⁴ composition,⁶³ or cell thickness,⁶⁴ utilizing reversible photochemical processes,^65,66 or applying Mechanical stress in cholesteric LC elastomers that are cross-linked, among others.⁶⁶

Applying electric fields to liquid crystal systems often produces a blue shift in lasing wavelength. This shift arises from the realignment of liquid crystal molecules, which changes the effective refractive index and subsequently alters the photonic band gap. Experimental results, such as those shown in Fig. 6, show that although blue shift is a general phenomenon in electrically tunable liquid crystal systems, its magnitude and nature are strongly influenced by system-specific factors. These include the composition of the liquid crystal matrix, the alignment conditions, and the type of dopants or nanoparticles used.

Fig. 6 (a) The band-gap tailored RL. (b) Transmission spectra of CLC as a function of temperature. (c) Random lasing spectra of cholesteric state at different NIR (850 nm) irradiation times. Reproduced with permission from ref. 67. Copyright 2018 Chinese Laser Press. (d) Schematic of an LC–polymer composite laser with a symmetric structure, where a dye-doped nematic LC (DDNLC) layer is enclosed between two polymer-stabilized cholesteric LC (PSCLC) layers. (e) Schematic diagram of the PBG-broadening mechanism of the PSCLC in the presence of dc voltage. Reproduced with permission from ref. 68. Copyright 2020 American Chemical Society.

Hu et al.⁶⁷ described the wavelength-tuned LCRL that resulted from the interaction of LC band-gap control and multiple scattering. Interestingly, scientists showed wavelength-tuned RLs rather than sideband lasers when heavily doped with chiral reagents and fluorescent dyes inside the liquid crystal system. This was because of the combined effects of band-gap control and multiple scattering of the cholesteric LC's flawed planar texture (Fig. 6a). The radiation spectra of the generated cholesteric LC cells at various temperatures are displayed in Fig. 6b. A redshift effect is seen in the band gap as temperature drops. Fig. 6c displays the random laser spectrum of cholesteric LCs at various NIR (850 nm) irradiation times. Furthermore, Zhang et al.⁶⁹ described using sunlight to power a chiral inversion, a full-wavelength tunable superstructure that softly controls the light wave by doping molecular motors into the liquid crystal mass.

A symmetric sandwich construction LC–polymer composite laser that can be controlled electrically was initially demonstrated by Lin et al.⁶⁸ The dye-doped nematic LC (DDNLC) film is placed between two identical polymers stabilized cholesteric LC (PSCLC) layers in this configuration. PSCLC and DDNLC layers function as half-wave plates using a medium for gain and dispersed Bragg reflectors. Due to electrically generated ion-concentration gradients, pitch gradients are created through both PSCLC layers simultaneously when the same voltage is applied (Fig. 6e). Pitch gradients rise in response to voltage increases, which causes the cell photonic band gap (PBG) to expand and the lasing wavelength to shift to the blue. The sandwiched cell PBG can reach over 170 nm, with a tuning range of up to 70 nm, as shown in Fig. 6d.¹³

Manipulation of random lasing threshold through liquid crystals

The threshold is a crucial metric for assessing the laser's performance parameters. The lower the threshold, the better for laser practical applications. The following components must be considered to generate low-threshold laser emission:

Defect structure. Random lasing in LCRL systems requires optical feedback from a scattering medium. In liquid crystal random laser systems, the dispersion and disarray within the system medium can be amplified by introducing faulty modes.⁷⁰ Twisted flaws were created by Masanori et al.⁷¹ utilizing two layers of photopolymerized cholesteric LC (PCLC) to create composite films. In dye-doped dual-composite PCLC films, low-threshold random lasing was discovered.

The excitation condition. Circular dichroism and optical rotatory dispersion are two well-known chiroptical phenomena induced in the ground state of molecules with the development of chiral enantiomerically pure groups and compounds. Because of their inherent twisting properties, selective light reflection is the most important characteristic these helical cholesteric LC structures display. For example, in a naturally right-handed cholesteric LC cell, linearly polarized light propagating along the helical axis results in the reflection and transmission of both right- and left-handed CPL. The threshold energy can be attained by selecting CPL in cholesteric liquid crystal lasing cells. According to Furumi et al.,⁷² CPL excitation, in contrast with the handedness of the cholesteric LC helix's molecular helical sense, reduced the threshold power compared to the same handedness of CPL excitation. Conversely, Matsuhisa et al.⁷³ stated that the same handedness of CP photoexcitation can be used to achieve a reduced threshold voltage when the wavelength of the excitation matches the photonic band-gap edge. This reflects the same result as Belyakov's prediction: photons dwell near the band gap edge for extended periods.⁷⁴

Cholesteric LC materials. The photonic band gap (PBG) width grows with the birefringence Δn. A CLC cell with a broader PBG width near the PBG band edge displays more conspicuous, tightly spaced, numerous internal reflections, decreasing the threshold energy and increasing the density of states value. Chee et al.⁷⁵ utilized three distinct nematic LC material types with varying optical birefringence anisotropy to create cholesteric LC cells. The study revealed that LC cells with a higher refractive index can significantly decrease the laser threshold energy.

Highly efficient dye molecules. Almost every LCRL studied to date has used store-bought laser dyes. Employing dyes with higher luminous efficiency is required to lower the threshold and boost the energy economy. A high-performance dye with exceptional solubility in cholesterol-containing LCs and increased luminescence efficiency was created by Uchimura et al.⁷⁶ In dye-doped distributed feedback cholesteric liquid crystal lasers, the use of such effective dyes allowed for a decrease in the laser threshold. When DCM dye is used, the threshold is lowered to one-twentieth of its initial worth.

Robust multi-scattering feedback. Many materials, including LCs, nanoparticles, and a pure laser dye solution, can supply the scattering mechanism. The feedback in RLs is produced by repeated photon scattering between disordered scattering particles; they lack a resonant cavity.⁷⁷ To produce RL radiation, there needs to be strong scattering and significant gain. To achieve this, the lasing threshold can be lowered by improving the system's dispersion. By applying 80 nm-thick conjugated polymer poly(2-methoxy-5-(20-ethyl-hexyloxy)-p-phenylenevinylene sheets to the substrate surface by spin-coating, Liu et al.⁷⁸ were able to create all-organic quasicrystals. Because of the intense scattering, the threshold was made more than twenty times lower when compared to traditional dye-doped quasicrystal microcavity lasers. Wan et al. showed the improvement of low-threshold random lasing in nematic LCs doped with dye in capillary tubes using Titanium Nitride nanoparticles.⁷⁹ The threshold for the pulse decreased to 2.37 mJ per pulse due to an increase in the density of TiN nanoparticles.

Manipulation of random lasing polarization through liquid crystals. Polarizing devices like Brewster windows or Lyot filters are often used to adjust the emission polarization of conventional lasers. Emission from polarized lasers is essential for useful applications. Light can be polarized in three ways: linearly, elliptically, and circularly.

There are currently three methods for achieving polarized random lasing: anisotropic waveguides,⁸⁰ anisotropic scattering,⁸¹ and anisotropic absorption.⁸² The direction of alignment for LC molecules often determines the polarization features of LC-based RLs. Rubbing and stress orientation are the two fundamental techniques used to fabricate the orientation of LC molecules. Stress, including stretching, shear, and compression, can affect the orientation of LC molecules, depending on the polymer mesh's flexibility and the optical anisotropy of nematic LC. This enables the regulation of the polarization degree and intensity of LCRL.

Yao et al.⁸³ in their study on dye-doped nematic LCs, examined LCRL polarization. The experimental results indicate that the output polarization of the LCRL is linked to both the LC director direction and the maximum scattering direction. Chen et al. investigated bidirectional LCRL fluorescence of an active twisted nematic LC with asymmetric polarization states.⁸⁴ The laser in this type uses a scattered feedback cavity and a polarization rotator as its main component (Fig. 7a). Lu et al.⁸⁵ created a polarization converter using photo-controlled orientation and a vector beam to produce random lasing emission, as seen in Fig. 7b. The generated converter can be used effectively as a polarization mask to create the vector light field in a simple experimental setup, as seen in Fig. 7c. The polarized LCRL emission was observed by Huang et al.,⁸⁶ who also discovered that polarized LCRLs with polarization orientations parallel to the LC molecules have less transmission loss due to the waveguide effect. A complicated ordered LC polymer film was successfully conceived and produced by Du et al.⁸⁷ This film was then developed into a holographic polarizer with a transmittance of more than 90%. With traditional absorptive and reflecting film polarizers having a transmittance of only about 45%, the holographic polarizer offers a great deal of promise for increasing the optical performance of polarizing optical systems. Each polarizer unit contained four LC polymer polarization grating regions with a grating vector directed toward a common centre. The structured PG was transformed into a holographic polarizer at a specific distance by creating a structured quarter wave plate (QWP) with two domains. The structured QWP was designed to convert circular polarization to linear polarization.¹³

Fig. 7 (a) Sketch depicting the emission of an RL from a twisted nematic film. Reproduced with permission from ref. 84. Copyright 2017 AIP Publishing. (b) Experimental configuration for vector light. Reproduced with permission from ref. 85. Copyright 2015 AIP Publishing. (c) LCM orientation and cell configuration. Reproduced with permission from ref. 86. Copyright 2021 Yunxi Huang et al., published by De Gruyter.

Emerging applications of liquid crystal RLs

This section explores the applications of liquid crystals, highlighting their unique features and significant contributions across various fields. These applications span medical imaging, environmental monitoring, quantum communication, and advanced display technologies. Fig. 8 provides a visual illustration of these diverse and emerging uses of liquid crystal-based technologies. The following subsections delve into the potential and impact of liquid crystal random lasers in these cutting-edge applications.

Fig. 8 Emerging applications of liquid crystal random lasers.

Liquid crystal laser displays

These technologies are useful in contemporary liquid crystal displays (LCDs), as they can use an external electric field to drive molecular reconfiguration in random lasers.^20,88 The screen's brightness can be efficiently changed by regulating the concentration of nanoparticles included in LC-based laser displays.⁸⁹ Cds semiconductor nanoparticle-based LC random lasers are used as optical components in photonic structures or holographic displays.⁹⁰

A saturated-colour laser display drawn on liquid crystals (LCs) was recently demonstrated. This innovation's idea involved creating a flat-panel design with a pixelated laser array using inkjet technology. Red, green, and blue (RGB) emissions from the LC-based arrays were carefully arranged on micro templates, resulting in a highly organized and single-mode functioning.⁹¹

The potential of cholesteric liquid crystals (LCs) in creating rewritable photonic paper has been thoroughly investigated. Yu et al. contributed significantly in this area by developing a novel method for writing, erasing, and—more significantly—adjusting the colours using light-driven cholesteric LCs.⁹²

Liquid crystals offer significant potential for creating pixelated laser display panels. The application of these panels faces challenges in manufacturing individual LC lasers and arranging them into regular red-green-blue pixel arrays.⁹³ To solve this problem, Zhao et al. suggested a cutting-edge strategy known as micro template-assisted inkjet printing. This method used pixelated LC microlaser arrays to create full-colour display screens. They exhibited full-colour displays using these ready LC micro laser pixel matrices as display panels.⁹¹

Furthermore, attention has recently been drawn increasingly to high-speed displays. Random lasers (RLs) appeal to such applications because they have higher switching speeds than traditional light-emitting diodes (LEDs). In addition, integrating emitters with various frequencies within the random medium makes a multi-colour display feasible. RLs can also function as operational components in various photonic components and circuits, expanding their range of potential applications.⁹⁴

Random lasing in diagnostics and therapy

Advancements in medical treatments and procedures have been made possible by using liquid crystal RLs in medical settings due to their high energy density emission and comparatively narrow linewidth. According to earlier studies^31,95 these traits have been crucial in opening up new opportunities for RLs in the medical industry.

The capacity of random lasers (RLs) to detect and track this “feel-good” neurotransmitter is useful as dopamine sensors. RLs have been used as a light source in photodynamic treatment to activate medicines first anchored to target cells. Applications in medical imaging, photodynamic therapy, and dermatology have profited from RL technology, especially in the tossing of unwelcome tattoos on the skin.⁹⁶

RL emission from dye-infiltrated human tissue was investigated by Polson et al. The findings revealed that cancerous or ill tissues possessed greater spectral lines than normal tissues. This discovery opened the door for diagnostic imaging, giving tumor diagnostics another tool.³¹ The potential uses of RLs in medicine were further expanded in 2010 by Qinghai Song et al., who used them to spot structural alterations in bone tissue at nanoscales.⁹⁷ The same year, R. C. Polson and Z. V. Vardeny revealed the mapping of malignant tissue using random lasing emission spectra analysis.⁹⁸ With an emphasis on cancer detection and medication administration, fluorescent colloidal silica nanoparticles (NPs) have found extensive use in various diagnostic and therapeutic applications.^99,100 Successful random lasing was demonstrated by Van Duong Ta et al. utilizing microslides made from self-assembled, dye-doped colloidal silica NPs. Their research illustrated how well a random laser works and how well it works in porcine skin tissue.¹⁰¹

The remarkable biocompatibility of silica-based lasers makes them ideal for incorporating into various biological components, including blood and tissue. This property opens up opportunities for using these lasers as probes to examine biological material in bioimaging and sensing.¹⁰²

Advanced LC-based sensing

The heat sensitivity of nematic liquid crystals (NLCs) makes them appropriate for remote thermal sensors, where the response signal can be examined using a telescope.²⁰ It has proven possible to make polymeric fiber optic random lasers, sensors, and displays by combining quantum dots (QDs) with nanoparticles.¹⁰³ Duan et al. have developed LC-based sensors with high sensitivity to urine molecules, capable of detecting molecular levels as low as 0.1 mM. Compared to older urea detectors, this device has various advantages, including real-time processing, quantifiable and accurate detection, and a higher resolution. These advantages are attributed to acid-doped 5CB liquid crystals using whispering gallery mode (WGM) laser technology. Due to the simultaneous light amplification and emission band shift by the LC microdroplets’ configuration change, such devices are excellent candidates for monitoring enzymatic processes.¹⁰⁴

There are numerous further uses in this area. A variety of biological substances, including lipids,¹⁰⁵ glucose,¹⁰⁶ and proteins¹⁰⁷ have been detected using LC-based sensors. They have also been used to detect synthetic polymers and heavy metal ions.^108,109 Furthermore, a functional microfiber humidity (RH) sensor has been successfully created by utilizing the synergistic impact of up-conversion nanoparticles (UCNPs) and cellulose LCs.

A biosensor for the detection of heavy metals (HMs) using LCs was recently introduced in a study. The variable lasing behaviour of the LC-based biosensor allowed for efficient detection. The whispering gallery mode (WGM) mechanism was implemented in the LC microdroplet sensor to provide a strong signal. Surprisingly, the WGM-enabled LC-based sensor exhibits selectivity in detecting light metal ions, preventing any potential interference from fake signals. This specific illustration can easily be used to evaluate drinking water quality or, more generally, observe environmental conditions.¹¹⁰

It is possible to link liquid crystals (LCs) with biological interactions by adding stimuli-responsive components into LCs. Because of their arrangement's exceptional sensitivity, LCs are highly sought-after for the creation of biosensors. These biosensors possess high sensitivity and enable the detection of label-free biomarkers at the water–liquid phase transition. Li et al. developed LC elastomer microspheres (LCEM-HRP) that were specifically modified with horse-radish peroxidase in their research. The ability of these microspheres to be directly attached to the cell membrane enables the real-time monitoring of H₂O₂ leakage at the single-cell level.¹¹¹

Due to their innate temperature sensitivity and biocompatibility, liquid crystal RLs have been used as remote temperature sensors and temperature-sensitive displays. The work of Wiersma et al., in which they developed a temperature-tunable RL, is a noteworthy example in this regard.¹¹²

Machine learning in random lasing

Integrating machine learning (ML) into random laser research has opened new ways to optimize laser properties and predict system behavior.¹¹³ ML algorithms have been successfully used to analyze complex datasets, enabling precise tuning of lasing thresholds and emission spectra. For example, neural networks have been used to model threshold behaviour in liquid crystal-based random lasers by learning from extensive experimental data. These networks can predict laser response under different conditions, such as changes in doping concentration or external fields.¹¹⁴

Support vector machines (SVMs) and decision tree algorithms have optimized external stimuli, such as electric fields, to achieve the desired laser characteristics. These methods reduce the trial-and-error aspect of experimentation and provide efficient ways to optimize parameters. A notable example is the application of supervised learning techniques to minimize laser thresholds by adjusting liquid crystal orientation and gain medium composition. Additionally, unsupervised ML algorithms such as clustering have been used to categorize emission spectra and identify trends and anomalies that may not be detectable through traditional analysis.

Integrating machine learning is particularly promising for addressing real-time laser control challenges, including tunability and stability in liquid crystal random lasers. As computational techniques advance, combining ML with experimental studies is expected to accelerate progress in random laser systems further and improve their applications in sensing, telecommunications, and photonic devices.¹¹⁵

Speckle-free imaging

As a potential use for random lasers, speckle-free bioimaging is extremely important. Speckle-free imaging is made possible by random lasers’ extraordinary brightness and low coherence.¹¹⁶

Traditional lasers produce speckled images due to the high coherence between several wavefronts, which causes interference patterns to appear. On the other hand, LEDs and other light sources with low coherence show a low photon count per coherence volume. Based on random lasing, a pulsed source with low spatial coherence has been designed to produce high-resolution, single-shot images with a uniform backdrop and little speckle noise.¹¹⁷ Using a bright narrowband light source with low coherence makes it possible to simultaneously capture the pitch and amplitude of the object and acquire high-quality photos free of speckle errors. The optical resolution of the microscope with time-resolved capabilities is maximized. This ground-breaking lighting technology improves the images’ dynamic range and signal-to-noise ratio. Due to the precise electronic coordination of the ultrafast and nanoscale laser systems, the stimulating ultrashort laser pulse in liquids and the randomly positioned light source utilized for probing can interact in a time-coordinated manner.¹¹⁸

The stimulating zone in the liquid specimen is captured using imaging in an inclined geometry. The microscope condenser and optical transmission bring the probe into the illumination path of the instrument. Consequently, back-illuminated electron multiplier EMCCDs capture phase contrast microscope pictures in the image plane. In such a case, the speckle-free pulsed imaging approach provides remarkable visualization quality for capturing the changing object's amplitude and phase features.¹¹⁹

Multi-control integration and micro photonics

Future integrative micro photonics research will focus on photon generation, transmission, and redirection properties. Electric fields can be used to accelerate and refocus electrons, but photons do not respond in the same way. As a result, harnessing the interconnection between matter and photons is necessary to manage the motion of photons. A promising method for gaining this control through altering chemistry and material properties is fluorescence, well-known for its quick and potent qualities. Fluorescence control is anticipated to be vital in creating quick and maybe ultrafast circuits in LC-integrated microphotonics that use self-sustaining LCs and other soft matter materials.¹²⁰ There is great potential for a single gadget that integrates several functionalities. For instance, azo dye-doped LCs and azobenzene^121,122 react to light and electric fields, respectively. These materials have greater control and flexibility because of their unique property.¹²³

Wearable and flexible technologies

Liquid crystal-based random lasers’ lightweight and flexible properties make them ideal for wearable applications. These systems can be integrated into smart textiles or wearable health devices to monitor physiological parameters in real-time. The tunability of random lasers enables adaptive sensing, ensuring accurate and responsive measurements of environmental or biological conditions. This innovation has potential applications in fitness tracking, personalized health monitoring, and even remote diagnostics.¹²⁴

Environmental monitoring

The fluorescence properties of liquid crystal random lasers enable their use as highly sensitive environmental sensors. With exceptional precision, these devices can detect pollutants such as heavy metals, pesticides, and volatile organic compounds in water, air, or soil.¹²⁵ Recent studies have investigated the role of the random laser in fluorescence-based heavy metal detection and demonstrated its ability to provide highly selective, real-time monitoring. This technology could play a crucial role in environmental protection and safety.¹²⁶

Quantum communication

The inherent randomness and unpredictability of emissions from liquid crystal-based random lasers make them promising candidates for safe light sources in quantum communication systems.¹²⁷ These lasers can be used for quantum key distribution (QKD), where randomness is critical to generating encryption keys. In addition, their low coherence properties reduce the risk of signal interception and thus increase security in sensitive communication networks.¹²⁸

Challenges and perspectives

Random lasing in liquid crystals has immense potential to revolutionize the development of photonic devices, with promising applications across various fields. However, unlocking the full capabilities of this technology requires addressing multiple challenges and pushing forward with innovative perspectives. One fundamental challenge is achieving tunability in laser output. While liquid crystals exhibit adaptable optical properties, precise control over lasing characteristics like wavelength and intensity remains complex. Dynamic tuning methods, including thermotropic adjustments (where temperature changes influence alignment and refractive index), external electric and magnetic field modulation, and hybrid systems that combine liquid crystals with photonic crystals or metamaterials, could be pivotal in enabling precise control of lasing parameters.^129,130

Electric and magnetic fields have different mechanisms for modulating the laser properties in liquid crystal-based random lasers. Electric fields interact primarily with the dipole moments of liquid crystal molecules, enabling precise control of lasing thresholds and wavelengths through birefringence changes and photonic band-gap tuning. This effect enables rapid and local adjustments, making electric fields extremely effective for dynamic tunability. Conversely, magnetic fields affect the magnetic anisotropy of liquid crystal molecules, which is typically weaker than their dielectric response.¹³¹ As a result, magnetic fields induce more gradual, widespread changes in molecular alignment, leading to more subtle modulation effects. While electric fields are better suited for fast and targeted modulation, magnetic fields offer non-contact control and are advantageous for bulk systems or environments sensitive to electrical interference. These complementary mechanisms highlight the versatility of liquid crystals in random laser applications, as demonstrated in studies comparing their influence on laser thresholds and spectral tunability.¹³²

Another significant challenge is ensuring stability and reliability, as LCRLs are highly sensitive to environmental factors like temperature, humidity, and electric fields. These variables can create inconsistencies in lasing, posing difficulties for practical use. Enhancing stability could involve developing robust liquid crystal formulations that are less prone to environmental changes, implementing encapsulation techniques to shield liquid crystals from external influences, and incorporating feedback mechanisms to autonomously regulate lasing properties in response to environmental shifts.¹³³

Expanding the application range of LCRLs is another significant opportunity. Beyond its traditional role in communication and display technologies, the distinct properties of random lasing could prove valuable in medical imaging, quantum communication, and environmental sensing. Polymers are highly versatile in their structure, physical, and chemical properties and are particularly promising for creating flexible and cost-effective random lasing devices. Advances in 3D printing technology also offer new possibilities, allowing LCRLs to be used in optofluidic, photonic circuits, and medical implants. Continued exploration of alternative methodologies could lead to the developing of low-cost, biocompatible devices for biomedical and environmental monitoring applications.¹¹⁹

Integrating LCRLs with existing photonic systems presents additional technical and engineering hurdles. Effective coupling with conventional optical fibres, sensors, and communication devices requires specialized optical interfaces, modular designs, and, ideally, industry-standard protocols to ensure compatibility across platforms. Progress in materials science also plays a central role in advancing LCRLs, as current liquid crystal materials exhibit gain efficiency and response time limitations. Exploring nanocomposites that include plasmonic nanoparticles or quantum dots may improve gain and broaden operational wavelengths, while synthetic techniques involving luminous metal nanoclusters combined with metamaterials show promise for stronger random lasing effects. For instance, silver nanoclusters demonstrate photon emission capabilities across both linear and nonlinear optical regimes, enabling wavelength tuning from picosecond to sub-microsecond scales and opening new avenues for applying these materials in random lasing systems.¹³⁴

Creating cutting-edge technologies that allow precise control of the emission direction in random lasers is an important and difficult goal. To do this, the random lasing mechanism can be enhanced with novel directional confinement elements. One such tactic is introducing confining elements that utilize hybrid polymer nanowires. When comprised in the random lasing system, these nanowires have the potential to provide emission directionality along their long axis. This finding would facilitate producing highly directed and controlled random laser outputs.¹³⁵

Controlling beam shape and coherence is another challenge, as LCRLs generally produce irregular beams with low coherence, limiting their use in applications needing directed or coherent light. Structured light emission, adaptive coherence control, and the integration of LCRLs with optical micro resonators or waveguides could improve these qualities, enabling greater precision in beam shape and directionality. Scaling up LCRL production also presents practical challenges, particularly in maintaining alignment consistency in mass manufacturing. Automated alignment techniques, cost-effective fabrication materials, and strategies for miniaturizing LCRLs for portable applications, such as wearable sensors or micro-displays, could facilitate their commercial viability.¹³⁶

Safety and regulatory compliance are critical for LCRLs, particularly in consumer and sensitive environments like healthcare. Establishing robust safety protocols and regulatory standards will ensure safe deployment. LCRLs hold potential in applications like non-destructive testing in manufacturing, where low power output reduces the risk of material damage. Furthermore, the multidisciplinary nature of LCRL research—spanning optics, materials science, and electronics—demands interdisciplinary collaboration, which can be challenging due to varied terminologies and methodologies. Collaborative research initiatives, standardized frameworks, and shared platforms for real-time interdisciplinary work could create a supportive environment to address the unique challenges of LCRL development.¹³⁷

In addition to these challenges, future LCRL research will benefit from exploring bottom-up and top-down synthesis techniques to develop more sophisticated devices. Integrating biocompatible materials, sustainable designs, and cutting-edge technologies such as 3D printing presents further opportunities to broaden LCRL applications, including optofluidic, photonic circuits, and medical implants. Moreover, emerging approaches, such as combining silver nanoclusters with two-dimensional matrices like graphene oxide nanosheets, offer exciting possibilities for high-efficiency random lasing. These advances, coupled with novel directional confinement elements like hybrid polymer nanowires, could enable precise emission control and facilitate the development of highly directed, controlled random lasers.

Conclusions

In conclusion, this thorough analysis highlights the significant progress made in random lasing in liquid crystals while underscoring the remaining challenges and open questions. Over the years, integrating nanoparticles, external fields, and innovative liquid crystal materials has led to key breakthroughs, advancing our understanding of random lasing mechanisms and enabling new possibilities for tunable optical devices. Despite these advancements, challenges such as optimizing lasing thresholds, enhancing emission stability, and improving system efficiency continue to hinder practical implementation.

The future of random lasing in liquid crystals holds tremendous potential. As materials science and nanotechnology evolve, novel nanoparticle doping and liquid crystal engineering approaches offer promising solutions to overcome current limitations. Furthermore, integrating external fields, such as electric or magnetic fields, can further enhance the tunability and functionality of these systems. These developments could pave the way for new applications, including tunable lasers for photonic circuits, light-based communication systems, optical sensors, and even biomedical diagnostics.

To fully realize this potential, a multi-disciplinary approach is essential. Collaboration among materials science, physics, chemistry, and engineering researchers will be key to developing the next generation of random lasing devices. Applying advanced computational techniques, such as machine learning and data-driven models, could also accelerate the optimization of random lasing properties, enabling more precise control over emission characteristics and threshold behaviour. By addressing the remaining challenges and leveraging the latest technological advancements, the field can transition from laboratory experiments to real-world applications.

Data availability

This review article does not contain any original data as it is based on an analysis and synthesis of existing literature. All information and findings presented are derived from published sources, which are appropriately cited throughout the manuscript. As such, no new data was generated or analyzed in the preparation of this article.

Conflicts of interest

There are no conflicts to declare.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (no. 62375200).

References

1. A. Siegman and H. Weichel, Am. J. Phys., 1974, 42, 521–523.
2. J. P. Gordon, H. J. Zeiger and C. H. Townes, Phys. Rev., 1955, 99, 1264.
3. R. Ambartsumyan, N. Basov, P. Kryukov and V. Letokhov, IEEE J. Quantum Electron., 1966, 2, 442–446.
4. V. Letokhov, Sov. Phys. JETP, 1968, 26, 835–840.
5. R. Ambartsumyan, N. Basov, P. Kryukov and V. Letokhov, Prog. Quantum Electron., 1970, 1, 107–185.
6. V. M. Markushev, V. Zolin and C. M. Briskina, Sov. J. Quantum Electron., 1986, 16, 281.
7. C. Gouedard, D. Husson, C. Sauteret, F. Auzel and A. Migus, J. Opt. Soc. Am. B, 1993, 10, 2358–2363.
8. W. Sha, C.-H. Liu and R. Alfano, Opt. Lett., 1994, 19, 1922–1924.
9. D. S. Wiersma, M. P. van Albada and A. Lagendijk, Nature, 1995, 373, 203–204.
10. N. Padiyakkuth, S. Thomas, R. Antoine and N. Kalarikkal, Mater. Adv., 2022, 6687–6706.
11. L. Zhou, T. Zhong, Y. Liu, T. Yu, K. Neyts, Z. Luo, H. Wang, J. Sun, J. Zhou and Y. Shen, Adv. Funct. Mater., 2024, 2404614.
12. Z. Xu, H. Zhang, C. Chen, G. Aziz, J. Zhang, X. Zhang, J. Deng, T. Zhai and X. Zhang, RSC Adv., 2019, 9, 28642–28647.
13. G. Qu, X. Zhang, S. Li, L. Lu, J. Gao, B. Yu, S. Wu, Q. Zhang and Z. Hu, Phys. Chem. Chem. Phys., 2023, 25, 48–63.
14. G. Huyet, M. Martinoni, J. Tredicce and S. Rica, Phys. Rev. Lett., 1995, 75, 4027.
15. R. Sakuraba, K. Iwakawa, K. Kanno and A. Uchida, Opt. Express, 2015, 23, 1470–1490.
16. F. Arecchi, G. Lippi, G. Puccioni and J. Tredicce, Opt. Commun., 1984, 51, 308–314.
17. V. Annovazzi-Lodi, S. Donati and M. Manna, IEEE J. Quantum Electron., 1994, 30, 1537–1541.
18. J. Mysliwiec, A. Szukalska, A. Szukalski and L. Sznitko, Nanophotonics, 2021, 10, 2309–2346.
19. T. Dudok and Y. A. Nastishin, Ukr. J. Phys. Opt., 2014, 47–67.
20. D. S. Wiersma, Nat. Phys., 2008, 4, 359–367.
21. N. A. I. M. Kamil, W. Z. W. Ismail, I. Ismail, S. R. Balakrishnan, M. A. Sahrim, J. Jamaludin, M. Othman and S. Suhaimi, AIP Conf. Proc., 2020, 2203, 020017.
22. W. Demtröder, Laser spectroscopy 1: basic principles, Springer, 2014.
23. O. Svelto and D. C. Hanna, Principles of lasers, Springer, 2010.
24. I. D. W. Samuel and G. A. Turnbull, Chem. Rev., 2007, 107, 1272–1295.
25. S. Chénais and S. Forget, Polym. Int., 2012, 61, 390–406.
26. W. M. Steen and J. Mazumder, Laser material processing, Springer science & business media, 2010.
27. F. Luan, B. Gu, A. S. Gomes, K.-T. Yong, S. Wen and P. N. Prasad, Nano Today, 2015, 10, 168–192.
28. H. Cao, Waves in random media, 2003, 13, R1.
29. T. Naruta, T. Akita, Y. Uchida, D. Lisjak, A. Mertelj and N. Nishiyama, Opt. Express, 2019, 27, 24426–24433.
30. A. S. Gomes, A. L. Moura, C. B. de Araújo and E. P. Raposo, Prog. Quantum Electron., 2021, 78, 100343.
31. R. C. Polson and Z. V. Vardeny, Appl. Phys. Lett., 2004, 85, 1289–1291.
32. H. Zhu, W. Zhang, J. Zhang, R. Ma, Z. Wang, Y. Rao and X. Li, Adv. Mater. Technol., 2021, 6, 2100562.
33. A. K. Augustine, P. Radhakrishnan, V. Nampoori and M. Kailasnath, Laser Phys. Lett., 2015, 12, 025006.
34. C. T. Dominguez, M. d A. Gomes, Z. S. Macedo, C. B. de Araújo and A. S. Gomes, Nanoscale, 2015, 7, 317–323.
35. E. Jimenez-Villar, V. Mestre, P. C. de Oliveira and G. F. de Sá, Nanoscale, 2013, 5, 12512–12517.
36. H. Cao, J. Y. Xu, Y. Ling, A. L. Burin, E. W. Seeling, X. Liu and R. P. Chang, IEEE J. Sel. Top. Quantum Electron., 2003, 9, 111–119.
37. H. Cao, J. Xu, S.-H. Chang and S. Ho, Phys. Rev. E: Stat., Nonlinear, Soft Matter Phys., 2000, 61, 1985.
38. W. Z. W. Ismail, D. Liu, S. Clement, D. W. Coutts, E. M. Goldys and J. M. Dawes, J. Opt., 2014, 16, 105008.
39. L. Sznitko, K. Cyprych, A. Szukalski, A. Miniewicz and J. Mysliwiec, Laser Phys. Lett., 2014, 11, 045801.
40. X. Wu, W. Fang, A. Yamilov, A. Chabanov, A. Asatryan, L. Botten and H. Cao, Phys. Rev. A: At., Mol., Opt. Phys., 2006, 74, 053812.
41. X. Wu and H. Cao, Opt. Lett., 2007, 32, 3089–3091.
42. D. S. Wiersma and S. Cavalieri, Phys. Rev. E: Stat., Nonlinear, Soft Matter Phys., 2002, 66, 056612.
43. J. F. Galisteo-López, M. Ibisate and C. López, J. Phys. Chem. C, 2014, 118, 9665–9669.
44. Q. Song, L. Liu, L. Xu, Y. Wu and Z. Wang, Opt. Lett., 2009, 34, 298–300.
45. K. L. Van der Molen, A. P. Mosk and A. Lagendijk, Opt. Commun., 2007, 278, 110–113.
46. K. L. van der Molen, A. P. Mosk and A. Lagendijk, Phys. Rev. A: At., Mol., Opt. Phys., 2006, 74, 053808.
47. Y. Ling, H. Cao, A. Burin, M. Ratner, X. Liu and R. Chang, Phys. Rev. A: At., Mol., Opt. Phys., 2001, 64, 063808.
48. M. C. A. de Oliveira, F. W. S. de Sousa Jr, F. A. Santos, L. M. Abegao, M. A. Alencar, J. J. Rodrigues Jr and H. P. de Oliveira, Opt. Mater., 2020, 101, 109722.
49. M. Leonetti and C. López, Appl. Phys. Lett., 2013, 102, 071105.
50. Y. Li, K. Xie, X. Zhang, Z. Hu, J. Ma, X. Chen, J. Zhang, Z. Liu and D. Chen, Photonic Sens., 2020, 10, 254–264.
51. F. Tommasi, E. Ignesti, L. Fini, F. Martelli and S. Cavalieri, Opt. Express, 2018, 26, 27615–27627.
52. E. Ignesti, F. Tommasi, L. Fini, S. Lepri, V. Radhalakshmi, D. Wiersma and S. Cavalieri, Phys. Rev. A: At., Mol., Opt. Phys., 2013, 88, 033820.
53. S. Fan, X. Zhang, Q. Wang, C. Zhang, Z. Wang and R. Lan, in Laser Applications in Microelectronic and Optoelectronic Manufacturing, 2009, vol. 7201, pp. 265–270.
54. S. Fan, X. Zhang, Q. Wang, C. Zhang, Z. Wang and R. Lan, J. Phys. D: Appl. Phys., 2008, 42, 015105.
55. J. Yi, G. Feng, L. Yang, K. Yao, C. Yang, Y. Song and S. Zhou, Opt. Commun., 2012, 285, 5276–5282.
56. X. Meng, K. Fujita, S. Murai, J. Konishi, M. Mano and K. Tanaka, Opt. Express, 2010, 18, 12153–12160.
57. J. Kitur, G. Zhu, M. Bahoura and M. Noginov, J. Opt., 2010, 12, 024009.
58. H. Cao, Y. Zhao, S. Ho, E. Seelig, Q. Wang and R. Chang, Phys. Rev. Lett., 1999, 82, 2278.
59. M. Born, E. Wolf and H. Haubold, Astron. Nachr., 1980, 301, 257.
60. H. Cao, Y. Ling, J. Xu, C. Cao and P. Kumar, Phys. Rev. Lett., 2001, 86, 4524.
61. S. Morris, A. Ford, C. Gillespie, M. Pivnenko, O. Hadeler and H. Coles, J. Soc. Inf. Disp., 2006, 14, 565–573.
62. A. Chanishvili, G. Chilaya, G. Petriashvili, R. Barberi, R. Bartolino, G. Cipparrone, A. Mazzulla, R. Gimenez, L. Oriol and M. Pinol, Appl. Phys. Lett., 2005, 86, 051107.
63. C.-T. Wang and T.-H. Lin, Opt. Express, 2008, 16, 18334–18339.
64. K. Sonoyama, Y. Takanishi, K. Ishikawa and H. Takezoe, Jpn. J. Appl. Phys., 2007, 46, L874.
65. A. Chanishvili, G. Chilaya, G. Petriashvili, R. Barberi, R. Bartolino, G. Cipparrone, A. Mazzulla and L. Oriol, Appl. Phys. Lett., 2003, 83, 5353–5355.
66. S. Furumi, S. Yokoyama, A. Otomo and S. Mashiko, Appl. Phys. Lett., 2004, 84, 2491–2493.
67. H. Lu, J. Xing, C. Wei, J. Xia, J. Sha, Y. Ding, G. Zhang, K. Xie, L. Qiu and Z. Hu, Photonics Res., 2018, 6, 390–395.
68. J.-D. Lin, Y.-S. Zhang, J.-Y. Lee, T.-S. Mo, H.-C. Yeh and C.-R. Lee, Macromolecules, 2020, 53, 913–921.
69. J. Zhang, F. Wang, S. Ghafoor, H. Wang, W. Zhang, K. Xie, R. Cheng, J. Yan, L. Niu and P. Wang, Adv. Opt. Mater., 2022, 10, 2200426.
70. M. Ozaki, R. Ozaki, T. Matsui and K. Yoshino, Jpn. J. Appl. Phys., 2003, 42, L472.
71. J. Schmidtke, W. Stille and H. Finkelmann, Phys. Rev. Lett., 2003, 90, 083902.
72. S. Furumi and Y. Sakka, Adv. Mater., 2006, 18, 775–780.
73. Y. Matsuhisa, Y. Huang, Y. Zhou, S.-T. Wu, R. Ozaki, Y. Takao, A. Fujii and M. Ozaki, Appl. Phys. Lett., 2007, 90, 091114.
74. V. Belyakov, Mol. Cryst. Liq. Cryst., 2006, 453, 43–69.
75. M. G. Chee, M. H. Song, D. Kim, H. Takezoe and I. J. Chung, Jpn. J. Appl. Phys., 2007, 46, L437.
76. M. Uchimura, Y. Watanabe, F. Araoka, J. Watanabe, H. Takezoe and G. I. Konishi, Adv. Mater., 2010, 22, 4473–4478.
77. L. Ye, Z. Yin, C. Zhao, C. Hou, Y. Wang, Y. Cui and Y. Lu, J. Mod. Opt., 2013, 60, 1607–1611.
78. Z. Liu, R. Chen, Y. Liu, X. Zhang, X. Sun, W. Huang and D. Luo, Opt. Express, 2017, 25, 21519–21525.
79. Y. Wan, Y. An and L. Deng, Sci. Rep., 2017, 7, 16185.
80. E. S. Leong, S. F. Yu, A. Abiyasa and S. P. Lau, Appl. Phys. Lett., 2006, 88, 091116.
81. Y. Ni, L. Gao, A. Miroshnichenko and C. Qiu, Opt. Express, 2013, 21, 8091–8100.
82. C. Wu, P. Tsay, H. Cheng and S. Bai, J. Appl. Phys., 2004, 95, 417–423.
83. F. Yao, W. Zhou, H. Bian, Y. Zhang, Y. Pei, X. Sun and Z. Lv, Opt. Lett., 2013, 38, 1557–1559.
84. C.-W. Chen, H.-P. Huang, H.-C. Jau, C.-Y. Wang, C.-W. Wu and T.-H. Lin, J. Appl. Phys., 2017, 121, 033102.
85. P. Chen, W. Ji, B.-Y. Wei, W. Hu, V. Chigrinov and Y.-Q. Lu, Appl. Phys. Lett., 2015, 107, 241102.
86. Y. Huang, X. Zhang, B. Yu, J. Ma, K. Xie, S. Cheng, J. Zhang and Z. Hu, Nanophotonics, 2021, 10, 3541–3547.
87. F. Fan, A. Tam, J. Sun and V. Chigrinov, Adv. Mater., 2015, 27, 7191–7195.
88. L. Ye, C. Zhao, Y. Feng, B. Gu, Y. Cui and Y. Lu, Nanoscale Res. Lett., 2017, 12, 1–8.
89. L.-W. Li, Z.-Z. Shang and L. Deng, Chin. Phys. B, 2016, 25, 090301.
90. L. Li, Optik, 2017, 134, 1–8.
91. F. F. Xu, Y. J. Li, Y. Lv, H. Dong, X. Lin, K. Wang, J. Yao and Y. S. Zhao, CCS Chem., 2020, 2, 369–375.
92. L. Qin, W. Gu, J. Wei and Y. Yu, Adv. Mater., 2018, 30, 1704941.
93. S. M. Morris, P. J. Hands, S. Findeisen-Tandel, R. H. Cole, T. D. Wilkinson and H. J. Coles, Opt. Express, 2008, 16, 18827–18837.
94. Y. Hou, Z. Zhou, C. Zhang, J. Tang, Y. Fan, F.-F. Xu and Y. S. Zhao, Sci. China Mater., 2021, 64, 2805–2812.
95. Q. Song, S. Xiao, Z. Xu, J. Liu, X. Sun, V. Drachev, V. M. Shalaev, O. Akkus and Y. L. Kim, Opt. Lett., 2010, 35, 1425–1427.
96. W. Z. W. Ismail, G. Liu, K. Zhang, E. M. Goldys and J. M. Dawes, Opt. Express, 2016, 24, A85–A91.
97. Q. Song, Z. Xu, S. H. Choi, X. Sun, S. Xiao, O. Akkus and Y. L. Kim, Biomed. Opt. Express, 2010, 1, 1401–1407.
98. R. Polson and Z. Vardeny, J. Opt., 2010, 12, 024010.
99. S. W. Bae, W. Tan and J.-I. Hong, Chem. Commun., 2012, 48, 2270–2282.
100. B. García-Ramiro, M. A. Illarramendi, S. García-Revilla, R. Balda, D. Levy, M. Zayat and J. Fernández, Appl. Phys. B: Lasers Opt., 2014, 117, 1135–1140.
101. T. T. Nguyen, T. H. L. Nghiem, H. N. Tran, A. T. Le, N. T. Dao, P. D. Duong and H. H. Mai, Opt. Commun., 2020, 475, 126207.
102. M. Peccianti, C. Conti, G. Assanto, A. De Luca and C. Umeton, Nature, 2004, 432, 733–737.
103. Z. Wang, M. Cao, G. Shao, Z. Zhang, H. Yu, Y. Chen, Y. Zhang, Y. Li, B. Xu and Y. Wang, J. Phys. Chem. Lett., 2020, 11, 767–774.
104. R. Duan, Y. Li, B. Shi, H. Li and J. Yang, Talanta, 2020, 209, 120513.
105. P. K. Mukherjee, J. Mol. Liq., 2014, 199, 133–136.
106. S. Zhong and C.-H. Jang, Biosens. Bioelectron., 2014, 59, 293–299.
107. V. K. Gupta, J. J. Skaife, T. B. Dubrovsky and N. L. Abbott, Science, 1998, 279, 2077–2080.
108. M. I. Kinsinger, B. Sun, N. L. Abbott and D. M. Lynn, Adv. Mater., 2007, 19, 4208–4212.
109. C.-H. Chen, Y.-C. Lin, H.-H. Chang and A. S.-Y. Lee, Anal. Chem., 2015, 87, 4546–4551.
110. R. Duan, Y. Li, H. Li and J. Yang, Biomed. Opt. Express, 2019, 10, 6073–6083.
111. W. Li, M. Khan, L. Lin, Q. Zhang, S. Feng, Z. Wu and J. M. Lin, Angew. Chem., 2020, 132, 9368–9373.
112. D. S. Wiersma and S. Cavalieri, Nature, 2001, 414, 708–709.
113. K. Li, R. Ma, Y. Qin, N. Gong, J. Wu, P. Wen, S. Tan, D. Z. Zhang, L. E. Murr and J. Luo, J. Mater. Process. Technol., 2023, 318, 118032.
114. G. Genty, L. Salmela, J. M. Dudley, D. Brunner, A. Kokhanovskiy, S. Kobtsev and S. K. Turitsyn, Nat. Photonics, 2021, 15, 91–101.
115. S. P. Murzin, X, International Conference on Information Technology and Nanotechnology (ITNT), 2024, pp. 1–6.
116. B. Redding, M. A. Choma and H. Cao, Nat. Photonics, 2012, 6, 355–359.
117. B. Redding, M. A. Choma and H. Cao, Opt. Lett., 2011, 36, 3404–3406.
118. I. Valov, R. Waser, J. R. Jameson and M. N. Kozicki, Nanotechnology, 2011, 22, 254003.
119. Y. T. Hsu, Y. Y. Lin, Y. Z. Chen, H. Y. Lin, Y. M. Liao, C. F. Hou, M. H. Wu, W. N. Deng and Y. F. Chen, Adv. Mater. Technol., 2020, 5, 1900742.
120. I. Muševič, Liq. Cryst. Rev., 2016, 4, 1–34.
121. T. Ikeda and O. Tsutsumi, Science, 1995, 268, 1873–1875.
122. W. C. Xu, S. Sun and S. Wu, Angew. Chem., Int. Ed., 2019, 58, 9712–9740.
123. S. Cui, L. Qin, X. Liu and Y. Yu, Adv. Opt. Mater., 2022, 10, 2102108.
124. Y. Xia, University of Glasgow, 2024.
125. F. Caroleo, G. Magna, M. L. Naitana, L. Di Zazzo, R. Martini, F. Pizzoli, M. Muduganti, L. Lvova, F. Mandoj and S. Nardis, Sensors, 2022, 22, 2649.
126. N. De Acha, C. Elosúa, J. M. Corres and F. J. Arregui, Sensors, 2019, 19, 599.
127. A. Sit, Université d’Ottawa/University of Ottawa, 2023.
128. M. Imran, A. B. Altamimi, W. Khan, S. Hussain and M. Alsaffar, IEEE Access, 2024, 12, 180048–180078.
129. E. Forsyth, D. A. Paterson, E. Cruickshank, G. J. Strachan, E. Gorecka, R. Walker, J. M. Storey and C. T. Imrie, J. Mol. Liq., 2020, 320, 114391.
130. J. Li, H. Nishikawa, J. Kougo, J. Zhou, S. Dai, W. Tang, X. Zhao, Y. Hisai, M. Huang and S. Aya, Sci. Adv., 2021, 7, eabf5047.
131. S. Gottardo, Universita’degli studi di Firenze & European Laboratory for Nonlinear Spectroscopy, 2004.
132. F. Ding, C. Meng and S. I. Bozhevolnyi, Photonics Insights, 2024, 3, R07–R07.
133. C.-C. Wang, M. Kataria, H.-I. Lin, A. Nain, H. Y. Lin, C. R. Paul Inbaraj, Y.-M. Liao, A. Thakran, H.-T. Chang and F.-G. Tseng, ACS Photonics, 2021, 8, 3051–3060.
134. I. Russier-Antoine, F. Bertorelle, R. Hamouda, D. Rayane, P. Dugourd, Ž. Sanader, V. Bonačić-Koutecký, P.-F. Brevet and R. Antoine, Nanoscale, 2016, 8, 2892–2898.
135. A. Portone, R. Borrego-Varillas, L. Ganzer, R. Di Corato, A. Qualtieri, L. Persano, A. Camposeo, G. Cerullo and D. Pisignano, ACS Nano, 2020, 14, 8093–8102.
136. P. Nancy, J. Jose, N. Joy, S. Valluvadasan, R. Philip, R. Antoine, S. Thomas and N. Kalarikkal, Nanomaterials, 2021, 11, 880.
137. F. Bertorelle, S. Basu, H. Fakhouri, M. P. Bakulić, P. Mignon, I. Russier-Antoine, P.-F. Brevet, S. Thomas, N. Kalarikkal and R. Antoine, Nano Express, 2020, 1, 030005.

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