Shanghai Institute of Optics and Fine Mechanics

The unique characteristics of ultrafast lasers, such as picosecond and femtosecond lasers, have opened up new avenues in materials processing that employ ultrashort pulse widths and extremely high peak intensities. Thus, ultrafast lasers are currently used widely for both fundamental research and practical applications. This review describes the characteristics of ultrafast laser processing and the recent advancements and applications of both surface and volume processing. Surface processing includes micromachining, micro- and nanostructuring, and nanoablation, while volume processing includes two-photon polymerization and three-dimensional (3D) processing within transparent materials. Commercial and industrial applications of ultrafast laser processing are also introduced, and a summary of the technology with future outlooks are also given. Scientists in Asia have reviewed the role of ultrafast lasers in materials processing. Koji Sugioka from RIKEN in Japan and Ya Cheng from the Shanghai Institute of Optics and Fine Mechanics in China describe how femtosecond and picosecond lasers can be used to perform useful tasks in both surface and volume processing. Such lasers can cut, drill and ablate a variety of materials with high precision, including metals, semiconductors, ceramics and glasses. They can also polymerize organic materials that contain a suitable photosensitizer and can three-dimensionally process inside transparent materials such as glass, and are already being used to fabricate medical stents, repair photomasks, drill ink-jet nozzles and pattern solar cells. The researchers also explain the characteristics of such lasers and the interaction of ultrashort, intense pulses of light with matter.

Few-layer black phosphorus (BP) is a new two-dimensional material which is of great interest for applications, mainly in electronics. However, its lack of environmental stability severely limits its synthesis and processing. Here we demonstrate that high-quality, few-layer BP nanosheets, with controllable size and observable photoluminescence, can be produced in large quantities by liquid phase exfoliation under ambient conditions in solvents such as N-cyclohexyl-2-pyrrolidone (CHP). Nanosheets are surprisingly stable in CHP, probably due to the solvation shell protecting the nanosheets from reacting with water or oxygen. Experiments, supported by simulations, show reactions to occur only at the nanosheet edge, with the rate and extent of the reaction dependent on the water/oxygen content. We demonstrate that liquid-exfoliated BP nanosheets are potentially useful in a range of applications from ultrafast saturable absorbers to gas sensors to fillers for composite reinforcement.

Employing high-yield production of layered materials by liquid-phase exfoliation, molybdenum disulfide (MoS2) dispersions with large populations of single and few layers were prepared. Electron microscopy verified the high quality of the two-dimensional MoS2 nanostructures. Atomic force microscopy analysis revealed that ~39% of the MoS2 flakes had thicknesses of less than 5 nm. Linewidth and frequency difference of the E(1)2g and A1g Raman modes confirmed the effective reduction of flake thicknesses from the bulk MoS2 to the dispersions. Ultrafast nonlinear optical (NLO) properties were investigated using an open-aperture Z-scan technique. All experiments were performed using 100 fs pulses at 800 nm from a mode-locked Ti:sapphire laser. The MoS2 nanosheets exhibited significant saturable absorption (SA) for the femtosecond pulses, resulting in the third-order NLO susceptibility Imχ((3)) ~ 10(-15) esu, figure of merit ~10(-15) esu cm, and free-carrier absorption cross section ~10(-17) cm(2). Induced free carrier density and the relaxation time were estimated to be ~10(16) cm(-3) and ~30 fs, respectively. At the same excitation condition, the MoS2 dispersions show better SA response than the graphene dispersions.

In the 2015 review paper ‘Petawatt Class Lasers Worldwide’ a comprehensive overview of the current status of high-power facilities of ${>}200~\text{TW}$ was presented. This was largely based on facility specifications, with some description of their uses, for instance in fundamental ultra-high-intensity interactions, secondary source generation, and inertial confinement fusion (ICF). With the 2018 Nobel Prize in Physics being awarded to Professors Donna Strickland and Gerard Mourou for the development of the technique of chirped pulse amplification (CPA), which made these lasers possible, we celebrate by providing a comprehensive update of the current status of ultra-high-power lasers and demonstrate how the technology has developed. We are now in the era of multi-petawatt facilities coming online, with 100 PW lasers being proposed and even under construction. In addition to this there is a pull towards development of industrial and multi-disciplinary applications, which demands much higher repetition rates, delivering high-average powers with higher efficiencies and the use of alternative wavelengths: mid-IR facilities. So apart from a comprehensive update of the current global status, we want to look at what technologies are to be deployed to get to these new regimes, and some of the critical issues facing their development.

Abstract A long debate on the charge identity and the associated mechanisms occurring in contact‐electrification (CE) (or triboelectrification) has persisted for many decades, while a conclusive model has not yet been reached for explaining this phenomenon known for more than 2600 years! Here, a new method is reported to quantitatively investigate real‐time charge transfer in CE via triboelectric nanogenerator as a function of temperature, which reveals that electron transfer is the dominant process for CE between two inorganic solids. A study on the surface charge density evolution with time at various high temperatures is consistent with the electron thermionic emission theory for triboelectric pairs composed of Ti–SiO 2 and Ti–Al 2 O 3 . Moreover, it is found that a potential barrier exists at the surface that prevents the charges generated by CE from flowing back to the solid where they are escaping from the surface after the contacting. This pinpoints the main reason why the charges generated in CE are readily retained by the material as electrostatic charges for hours at room temperature. Furthermore, an electron‐cloud–potential‐well model is proposed based on the electron‐emission‐dominatedcharge‐transfer mechanism, which can be generally applied to explain all types of CE in conventional materials.

We show that short-pulse laser-induced classical ripples on dielectrics, semiconductors, and conductors exhibit a prominent "non-classical" characteristic-in normal incidence the periods are definitely smaller than laser wavelengths, which indicates that the simplified scattering model should be revised. Taking into account the surface plasmons (SPs), we consider that the ripples result from the initial direct SP-laser interference and the subsequent grating-assisted SP-laser coupling. With the model, the period-decreasing phenomenon originates in the admixture of the field-distribution effect and the grating-coupling effect. Further, we propose an approach for obtaining the dielectric constant, electron density, and electron collision time of the high-excited surface. With the derived parameters, the numerical simulations are in good agreement with the experimental results. On the other hand, our results confirm that the surface irradiated by short-pulse laser with damage-threshold fluence should behave metallic, no matter for metal, semiconductor, or dielectric, and the short-pulse laser-induced subwavelength structures should be ascribed to a phenomenon of nano-optics.

Since their inception in the 1930–1960s, the research disciplines of computational imaging and machine learning have followed parallel tracks and, during the last two decades, experienced explosive growth drawing on similar progress in mathematical optimization and computing hardware. While these developments have always been to the benefit of image interpretation and machine vision, only recently has it become evident that machine learning architectures, and deep neural networks in particular, can be effective for computational image formation, aside from interpretation. The deep learning approach has proven to be especially attractive when the measurement is noisy and the measurement operator ill posed or uncertain. Examples reviewed here are: super-resolution; lensless retrieval of phase and complex amplitude from intensity; photon-limited scenes, including ghost imaging; and imaging through scatter. In this paper, we cast these works in a common framework. We relate the deep-learning-inspired solutions to the original computational imaging formulation and use the relationship to derive design insights, principles, and caveats of more general applicability. We also explore how the machine learning process is aided by the physics of imaging when ill posedness and uncertainties become particularly severe. It is hoped that the present unifying exposition will stimulate further progress in this promising field of research. ©2019 Optical Society of America.

Entangled-photon coincidence imaging is a method to nonlocally image an object by transmitting a pair of entangled photons through the object and a reference optical system, respectively. The image of the object can be extracted from the coincidence rate of these two photons. From a classical perspective, the image is proportional to the fourth-order correlation function of the wave field. Using classical statistical optics, we study a particular aspect of coincidence imaging with incoherent sources. As an application, we give a proposal to realize lensless Fourier-transform imaging, and discuss its applicability in x-ray diffraction.

The rapid development of the femtosecond laser has revolutionized materials processing due to its unique characteristics of ultrashort pulse width and extremely high peak intensity. The short pulse width suppresses the formation of a heat-affected zone, which is vital for ultrahigh precision fabrication, whereas the high peak intensity allows nonlinear interactions such as multiphoton absorption and tunneling ionization to be induced in transparent materials, which provides versatility in terms of the materials that can be processed. More interestingly, irradiation with tightly focused femtosecond laser pulses inside transparent materials makes three-dimensional (3D) micro-and nanofabrication available due to efficient confinement of the nonlinear interactions within the focal volume. Additive manufacturing (stereolithography) based on multiphoton absorption (two-photon polymerization) enables the fabrication of 3D polymer micro-and nanostructures for photonic devices, micro-and nanomachines, and microfluidic devices, and has applications for biomedical and tissue engineering. Subtractive manufacturing based on internal modification and fabrication can realize the direct fabrication of 3D microfluidics, micromechanics, microelectronics, and photonic microcomponents in glass. These microcomponents can be easily integrated in a single glass microchip by a simple procedure using a femtosecond laser to realize more functional microdevices, such as optofluidics and integrated photonic microdevices. The highly localized multiphoton absorption of a tightly focused femtosecond laser in glass can also induce strong absorption only at the interface of two closely stacked glass substrates. Consequently, glass bonding can be performed based on fusion welding with femtosecond laser irradiation, which provides the potential for applications in electronics, optics, microelectromechanical systems, medical devices, microfluidic devices, and small satellites. This review paper describes the concepts and principles of femtosecond laser 3D micro-and nanofabrication and presents a comprehensive review on the state-of-the-art, applications, and the future prospects of this technology.

Most of the neural networks proposed so far for computational imaging (CI) in optics employ a supervised training strategy, and thus need a large training set to optimize their weights and biases. Setting aside the requirements of environmental and system stability during many hours of data acquisition, in many practical applications, it is unlikely to be possible to obtain sufficient numbers of ground-truth images for training. Here, we propose to overcome this limitation by incorporating into a conventional deep neural network a complete physical model that represents the process of image formation. The most significant advantage of the resulting physics-enhanced deep neural network (PhysenNet) is that it can be used without training beforehand, thus eliminating the need for tens of thousands of labeled data. We take single-beam phase imaging as an example for demonstration. We experimentally show that one needs only to feed PhysenNet a single diffraction pattern of a phase object, and it can automatically optimize the network and eventually produce the object phase through the interplay between the neural network and the physical model. This opens up a new paradigm of neural network design, in which the concept of incorporating a physical model into a neural network can be generalized to solve many other CI problems.

Information security and authentication are important challenges facing society. Recent attacks by hackers on the databases of large commercial and financial companies have demonstrated that more research and development of advanced approaches are necessary to deny unauthorized access to critical data. Free space optical technology has been investigated by many researchers in information security, encryption, and authentication. The main motivation for using optics and photonics for information security is that optical waveforms possess many complex degrees of freedom such as amplitude, phase, polarization, large bandwidth, nonlinear transformations, quantum properties of photons, and multiplexing that can be combined in many ways to make information encryption more secure and more difficult to attack. This roadmap article presents an overview of the potential, recent advances, and challenges of optical security and encryption using free space optics. The roadmap on optical security is comprised of six categories that together include 16 short sections written by authors who have made relevant contributions in this field. The first category of this roadmap describes novel encryption approaches, including secure optical sensing which summarizes double random phase encryption applications and flaws [Yamaguchi], the digital holographic encryption in free space optical technique which describes encryption using multidimensional digital holography [Nomura], simultaneous encryption of multiple signals [Prez-Cabr], asymmetric methods based on information truncation [Nishchal], and dynamic encryption of video sequences [Torroba]. Asymmetric and one-way cryptosystems are analyzed by Peng. The second category is on compression for encryption. In their respective contributions, Alfalou and Stern propose similar goals involving compressed data and compressive sensing encryption. The very important area of cryptanalysis is the topic of the third category with two sections: Sheridan reviews phase retrieval algorithms to perform different attacks, whereas Situ discusses nonlinear optical encryption techniques and the development of a rigorous optical information security theory. The fourth category with two contributions reports how encryption could be implemented at the nano-or micro-scale. Naruse discusses the use of nanostructures in security applications and Carnicer proposes encoding information in a tightly focused beam. In the fifth category, encryption based on ghost imaging using single-pixel detectors is also considered. In particular, the authors [Chen, Tajahuerce] emphasize the need for more specialized hardware and image processing algorithms. Finally, in the sixth category, Mosk and Javidi analyze in their corresponding papers how quantum imaging can benefit optical encryption systems. Sources that use few photons make encryption systems much more difficult to attack, providing a secure method for authentication. S Online supplementary data available from stacks.iop.org/JOPT/18/083001/mmedia (Some figures may appear in colour only in the online journal) Contents I. Encryption technologies 1. Secure optical sensing 4 2. Digital holographic encryption in free space optical technique 6 3. Simultaneous encryption and authentication of multiple signals 8 4. Amplitude-and phase-truncation based optical asymmetric cryptosystem 10 5. Optical security: dynamical processes and noise-free recovery 12

In this manuscript, we propose a novel framework of computational ghost imaging, i.e., ghost imaging using deep learning (GIDL). With a set of images reconstructed using traditional GI and the corresponding ground-truth counterparts, a deep neural network was trained so that it can learn the sensing model and increase the quality image reconstruction. Moreover, detailed comparisons between the image reconstructed using deep learning and compressive sensing shows that the proposed GIDL has a much better performance in extremely low sampling rate. Numerical simulations and optical experiments were carried out for the demonstration of the proposed GIDL.

The optical nonlinearity of WS2 and MoS2 monolayer and few-layer films was investigated using the Z-scan technique with femtosecond pulses from the visible to the near-infrared range. The nonlinear absorption of few- and multilayer WS2 and MoS2 films and their dependences on excitation wavelength were studied. WS2 films with 1-3 layers exhibited a giant two-photon absorption (TPA) coefficient as high as (1.0 ± 0.8) × 10(4) cm/GW. TPA saturation was observed for the WS2 film with 1-3 layers and for the MoS2 film with 25-27 layers. The giant nonlinearity of WS2 and MoS2 films is attributed to a two-dimensional confinement, a giant exciton effect, and the band edge resonance of TPA.

Knowledge gained through x-ray crystallography fostered structural determination of materials and greatly facilitated the development of modern science and technology in the past century. However, it is only applied to crystalline structures and cannot resolve noncrystalline materials. Here we demonstrate a novel lensless Fourier-transform ghost imaging method with pseudothermal hard x rays that extends x-ray crystallography to noncrystalline samples. By measuring the second-order intensity correlation function of the light, Fourier-transform diffraction pattern of a complex amplitude sample is achieved at the Fresnel region in our experiment and the amplitude and phase distributions of the sample in the spatial domain are retrieved successfully. For the first time, ghost imaging is experimentally realized with x rays. Since a highly coherent x-ray source is not required, the method can be implemented with laboratory x-ray sources and it also provides a potential solution for lensless diffraction imaging with fermions, such as neutrons and electrons where intensive coherent sources usually are not available.

A series of layered molybdenum dichalcogenides, i.e., MoX₂ (X = S, Se and Te), were prepared in cyclohexyl pyrrolidinone by a liquid-phase exfoliation technique. The high quality of the two-dimensional nanostructures was verified by transmission electron microscopy and absorption spectroscopy. Open- and closed-aperture Z-scans were employed to study the nonlinear absorption and nonlinear refraction of the MoX₂ dispersions, respectively. All the three-layered nanostructures exhibit prominent ultrafast saturable absorption (SA) for both femtosecond (fs) and picosecond (ps) laser pulses over a broad wavelength range from the visible to the near infrared. While the dispersions treated with low-speed centrifugation (1500 rpm) have an SA response, and the MoS₂ and MoSe₂ dispersions after higher speed centrifugation (10,000 rpm) possess two-photon absorption for fs pulses at 1030 nm, which is due to the significant reduction of the average thickness of the nanosheets; hence, the broadening of band gap. In addition, all dispersions show obvious nonlinear self-defocusing for ps pulses at both 1064 nm and 532 nm, resulting from the thermally-induced nonlinear refractive index. The versatile ultrafast nonlinear properties imply a huge potential of the layered MoX2 semiconductors in the development of nanophotonic devices, such as mode-lockers, optical limiters, optical switches, etc.

Two-dimensional (2D) nanomaterials, especially the transition metal sulfide semiconductors, have drawn great interests due to their potential applications in viable photonic and optoelectronic devices. In this work, 2D tungsten disulfide (WS2) based saturable absorber (SA) for ultrafast photonic applications was demonstrated. WS2 nanosheets were prepared using liquid-phase exfoliation method and embedded in polyvinyl alcohol (PVA) thin film for the practical usage. Saturable absorption was discovered in the WS2-PVA SA at the telecommunication wavelength near 1550 nm. By incorporating WS2-PVA SA into a fiber laser cavity, both stable mode locking operation and Q-switching operation were achieved. In the mode locking operation, the laser obtained femtosecond output pulse width and high spectral purity in the radio frequency spectrum. In the Q-switching operation, the laser had tunable repetition rate and output pulse energy of a few tens of nano joule. Our findings suggest that few-layer WS2 nanosheets embedded in PVA thin film are promising nonlinear optical materials for ultrafast photonic applications as a mode locker or Q-switcher.

Ghost imaging (GI) facilitates image acquisition under low-light conditions by single-pixel measurements and thus has great potential in applications in various fields ranging from biomedical imaging to remote sensing. However, GI usually requires a large amount of single-pixel samplings in order to reconstruct a high-resolution image, imposing a practical limit for its applications. Here we propose a far-field super-resolution GI technique that incorporates the physical model for GI image formation into a deep neural network. The resulting hybrid neural network does not need to pre-train on any dataset, and allows the reconstruction of a far-field image with the resolution beyond the diffraction limit. Furthermore, the physical model imposes a constraint to the network output, making it effectively interpretable. We experimentally demonstrate the proposed GI technique by imaging a flying drone, and show that it outperforms some other widespread GI techniques in terms of both spatial resolution and sampling ratio. We believe that this study provides a new framework for GI, and paves a way for its practical applications.

Crystalline lithium niobate (LN) is an important optical material because of its broad transmission window that spans from ultraviolet to mid-infrared and its large nonlinear and electro-optic coefficients. Furthermore, the recent development and commercialization of LN-on-insulator (LNOI) technology has opened an avenue for the realization of integrated on-chip photonic devices with unprecedented performances in terms of propagation loss, optical nonlinearity, and electro-optic tunability. This review begins with a brief introduction of the history and current status of LNOI photonics. We then discuss the fabrication techniques of LNOI-based photonic structures and devices. The recent revolution in the LN photonic industry has been sparked and is still being powered by innovations of the nanofabrication technology of LNOI, which enables the production of building block structures, such as optical microresonators and waveguides of unprecedented optical qualities. The following sections present various on-chip LNOI devices categorized into nonlinear photonic and electro-optic tunable devices and photonic-integrated circuits. Some conclusions and future perspectives are provided.

For remote sensing, high-resolution imaging techniques are helpful to catch more characteristic information of the target. We extend pseudo-thermal light ghost imaging to the area of remote imaging and propose a ghost imaging lidar system. The experimental results demonstrate that the real-space image of a target at about 1.0 km range with 20 mm resolution is achieved by ghost imaging via sparsity constraints (GISC) technique. The characters of GISC technique compared to the existing lidar systems are also discussed.

Near infrared broadband emission characteristics of bismuth-doped aluminophosphate glass have been investigated. Broad infrared emissions peaking at 1210nm, 1173nm and 1300nm were observed when the glass was pumped by 405nm laser diode (LD), 514nm Ar+ laser and 808nm LD, respectively. The full widths at half maximum (FWHMs) are 235nm, 207nm and 300nm for the emissions at 1210nm, 1173nm and 1300nm, respectively. Based on the energy matching conditions, it is suggested that the infrared emission may be ascribed to 3P1? 3P0 transition of Bi+. The broadband infrared luminescent characteristics of the glasses indicate that they are promising for broadband optical fiber amplifiers and tunable lasers.