Toluene and dichloromethane, as representative volatile organic compounds (VOCs) emissions from industrial exhaust gases, have attracted significant scientific attention. This study employs density functional theory (DFT) to investigate the adsorption mechanisms of toluene and dichloromethane on pristine anatase TiO2(001) and its Ce-doped + CuO-doped surfaces. Results demonstrate that toluene undergoes stable chemisorption on the TiO2(001) surface. Adsorption is significantly enhanced on both Ce/TiO2(001) and CuO/TiO2(001) modified surfaces, characterized by strong electron transfer and stable bonding. The toluene molecule undergoes unstable structural changes on the Ce/TiO2(001) substrate and eventually forms strong chemical bonds with the substrate atoms, indicating a strong adsorption capacity, with an adsorption energy of-190.578 kJ/mol. Dichloromethane also exhibits chemisorption, particularly on Ce/TiO2(001) and oxygen-bridge CuO/TiO2(001) surfaces, where it undergoes dechlorination to form Cl and chloromethyl radicals (CH2Cl center dot). These radicals subsequently form stable chemical bonds with the surface. The high adsorption energy of dichloromethane on Ce/TiO2(001) (-510.5 kJ/ mol) confirms strong chemisorption. Dechlorination of dichloromethane, producing free Cl that establish stable chemical bonds with Ce atoms, is more advantageous both thermodynamically and kinetically. Subsequently, the CH2Cl center dot undergoes an oxidation reaction, with a hydrogen atom being released.

Multimode fibers are promising for compact imaging and spectroscopy. However, current implementations are typically limited to a single function and often lack robustness against environmental disturbances. Unlike approaches that solely analyze the fiber end-face, we exploit the high information density of the leaky field from a fiber taper. A lensless system with a deep learning framework is developed, simultaneously capturing multi-modal data from the taper leaky field and the end-face speckle. This approach achieves spectral reconstruction with a resolution of 0.05 nm and enables high-quality image recovery. By fusing both light fields, we significantly enhance image quality (MNIST SSIM up to 0.99), demonstrating a robust, all-fiber platform for integrated spectroscopic and imaging applications. (c) 2026 Chinese Laser Press

High-precision metrology has laid the foundation for semiconductor fabrication and life sciences. However, existing displacement measurement approaches are incapable of performing flexible probing within complex equipment interiors. Here, we present a in situ, non-contact nano-displacement measurement approach. Leveraging a multimode fiber probe empowered by deep learning, fine feature information can be efficiently extracted from superoscillatory speckles, achieving single-ended detection with 10 nm resolution and 99.95% accuracy. A physical model is established to correlate the displacement with higher-order modes proportion in the fiber. Sub-millimeter-sized probe enables detecting targets with different structures in confined spaces. Robust recognition is achieved through joint learning, under varying fiber bending conditions and different metal materials. With extreme compression ratios of less than 0.1%, the system delivers high accuracy, low training costs, and high-speed processing. The imaging capability of the probe is also experimentally validated, proving potential as a powerful tool in applications such as lithography, weak force sensing, and super-resolution micro-endoscopy.

The evolution of soft robots into embodied intelligent systems relies fundamentally on precise proprioception. However, a universal solution for capturing continuous deformations during diverse interactions, particularly in spatially confined interventional scenarios, remains lacking. Here, we introduce a deep learning-enabled versatile shape perception method based on a single-ended multimode fiber (MMF). By leveraging the intrinsic integration advantages of optics, our minimalist reflective architecture physically eliminates the dependence on complex demodulation units and distal devices. Furthermore, treating chaotic optical speckle fields as data streams encoding high-dimensional shape information, reconfigurable neural decoders resolve a single physical channel into versatile perception modes tailored to heterogeneous tasks: discrete state confirmation on soft grippers (>99% accuracy), continuous shape tracking on bionic dexterous hands (~5-fold spatial resolution enhancement), and intuitive 3D morphological reconstruction of soft surgical robots (IoU>0.93). Overall, our work establishes a versatile framework for breaking hardware adaptability limits via computation, laying a solid foundation for closed-loop control in digital twins of soft robots.

Image transmission through multimode fibers (MMFs) poses a complex inversion challenge due to the intricate light transport and potential information loss. While recent advances in deep neural networks (DNNs) have shown promise in modeling the MMF input‐output relationship, commonly‐used networks such as fully connected (FC) models and convolutional neural networks (CNNs) fall short of leveraging the inherent sparsity of MMF systems, which leads to learning inefficiency and poor angular generalization. Here, an ultra‐compact Radon transform‐facilitated cross‐domain learning framework, called Radon Transmission network (RTMnet), is presented. Inspired by the physical sparsity in MMF's rotational memory effect, the Radon transform is applied to the captured speckle and performs physics‐guided learning of MMF image transmission in the sinogram domain. RTMnet enables high‐fidelity MMF image transmission with an order‐of‐magnitude reduction in computational demand compared to traditional DNN models. Arbitrarily rotated handwritten digit images can be faithfully reconstructed using a limited training data of only 7000 non‐rotated digits. This enhancement in learning efficiency underscores RTMnet's physics consistency and its potential to effectively generalize in resource‐constrained fiber‐based applications such as miniaturized endoscopy systems.

The generation and deposition of ammonium bisulfate (ABS) contribute to the exacerbation of the air preheater clogging issue, which has a detrimental impact on the safe and cost-effective operation of coal-fired power plants. This study examined the effects of ABS deposition and temperature on fly ash adhesion. The greater the quantity of ABS deposited in the fly ash, the stronger the adhesion of the fly ash. Physical action (liquid ABS) demonstrated a more pronounced effect on enhancing fly ash adhesion capacity than chemical action. At 220 degrees C, the enhancement of fly ash adhesion by liquid ABS was the greatest. ABS is physically adsorbed to the particles and then acts on the surface of the particles, resulting in a change in particle size. The ABS undergoes a chemical reaction with the fly ash, forming sulfate products such as CaSO4 and Fe2(SO4)3, which are adsorbed on the surface of the particles. The preferred reaction order between ABS and the various components of the fly ash is the first reaction with CaO. The formation of potassium alum, a substance with a low melting point, is promoted by ABS. This study constructed a model of non-catalytic ABS adhesion opportunities in the air preheater to provide theoretical guidance for subsequent effective prevention or mitigation of air preheater clogging.

The all-fiber lensless microimaging scheme was experimentally demonstrated for the first time. Natural scenes reconstruction and distance detection are implemented with dual networks and partially diffuse speckles. Highly integrated structure is suitable for implantable micro-endoscopes.

Optical skyrmions are an emerging class of structured light with sophisticated particle-like topologies with great potential for revolutionizing modern informatics. However, the current generation of optical skyrmions involves complex or bulky systems, hindering their development of practical applications. Here, exploiting the emergent "lab-on-fiber" technology, we demonstrate the design of a metafiber-integrated photonic skyrmion generator. We not only successfully generated high-quality optical skyrmions from metafibers, but also experimentally verified their remarkable properties, such as regulability and topological stability with deep-subwavelength features beyond the diffraction limits. Our flexible and fiber-integrated optical skyrmions platform paves the avenue for future applications of topologically-enhanced remote super-resolution microscopy and super-robust information transfer.

In the realm of spatial information transmission in multimode fiber (MMF), the MMF-based endoscopes and information encryption technologies have garnered considerable attention. However, existing designs are limited to establishing a single connection between one input node and one output node, thus constraining the capacity and application scenarios of MMF spatial information transmission. Here, we demonstrate a new concept of MMF-based physical networking for spatial information transmission, and develop a physical model and implementation method for establishing multi-node networking with various topological structures via cascading MMFs.We experimentally verify the feasibility of parallel transmission of spatial information at multiple nodes in an exemplary three-node MMF network with chain topology, showcasing its capability in transmitting color images through "node multiplexing" with significantly enhanced communication security through long-distance reprogrammable optical encryption. Designing MMF networks based on different node quantities and topological structures can significantly expand the scenarios for MMF spatial information transmission, providing valuable paradigms for various applications such as minimally invasive panoramic endoscopy, low-cost distributed sensing, and scaling optical reservoir computing.

Considering the obvious application value in the field of minimally invasive and non-destructive clinical healthcare, we explore the challenge of wide-field imaging and recognition through cascaded complex scattering media, a topic that has been less researched, by realizing wide-field imaging and pathological screening through multimode fibers (MMF) and turbid media. To address the challenge of extracting features from chaotic and globally correlated speckles formed by transmitting images through cascaded complex scattering media, we establish a deep learning approach based on SMixerNet. By efficiently using the parameter-free matrix transposition, SMixerNet achieves a broad receptive field with less inductive bias through concise multi-layer perceptron (MLP). This approach circumvents the parameter's intensive requirements of previous implementations relying on self-attention mechanisms for global receptive fields. Imaging and pathological screening results based on extensive datasets demonstrate that our approach achieves better performance with fewer learning parameters, which helps deploy deep learning models on desktop-level edge computing devices for clinical healthcare. Our research shows that, deep learning facilitates imaging and recognition through cascaded complex scattering media. This research extends the scenarios of medical and industrial imaging, offering additional possibilities in minimally invasive and non-destructive clinical healthcare and industrial monitoring in harsh and complex scenarios.

We introduce random laser into a single-fiber image transmission system for the first time. High-quality transmission of complex grayscale patterns is achieved with inverse transmission matrix. It provides guidance for fiber imaging and flexible endoscopy.

Optical skyrmions are an emerging class of structured light with sophisticated particle-like topologies with great potential for revolutionizing modern informatics. However, the current generation of optical skyrmions involves complex or bulky systems, hindering the development of practical applications. Here, exploiting the emergent "lab-on-fiber" technology, we demonstrate the design of a metafiber-integrated photonic skyrmion generator. We not only successfully generate high-quality optical skyrmions from metafibers, but also verify their remarkable properties, such as topology switchability and topology stability with subwavelength polarization features beyond the diffraction limits. Our flexible fiber-integrated optical skyrmions platform paves the avenue for future applications of topologically-enhanced remote super-resolution microscopy and robust information transfer. Current optical skyrmion generators involve complex bulky systems, hindering further practical applications. We propose an integrated metafiber for high-quality photonic skyrmions, with subwavelength polarization features and topology tunability.

Multimode fiber (MMF) is extensively studied for its ability to transmit light modes in parallel, potentially minimizing optical fiber size in imaging. However, current research predominantly focuses on grayscale imaging, with limited attention to color studies. Existing colorization methods often involve costly white light lasers or multiple light sources, increasing optical system expenses and space. To achieve wide-field color images with typical monochromatic illumination MMF imaging system, we proposed a data-driven "colorization" approach and a neural network called SpeckleColorNet, merging U-Net and conditional GAN (cGAN) architectures, trained by a combined loss function. This approach, demonstrated on a 2-meter MMF system with single-wavelength illumination and the Peripheral Blood Cell (PBC) dataset, outperforms grayscale imaging and alternative colorization methods in readability, definition, detail, and accuracy. Our method aims to integrate MMF into clinical medicine and industrial monitoring, offering cost-effective high-fidelity color imaging. It serves as a plug-and-play replacement for conventional grayscale algorithms in MMF systems, eliminating the need for additional hardware.

The transition metal-modified VWTi structural catalysts hold great promise for simultaneously removing nitrogen oxides (NOx) and volatile organic compounds (VOCs) from industrial flue gases. A series of Cu@VWTi catalysts were prepared to investigate their synergistic low-temperature removal performance towards NO and typical VOCs, including toluene, benzene, chlorobenzene (CB), p-chlorotoluene (p-CT), and dichloromethane (DCM). The copper-enhanced samples prepared via ultrasound-assisted impregnation exhibited irregular globular and varying crystallinity. The catalysts displayed a typical anatase crystal structure with high TiO2 content or high dispersion of V and W species along with a certain adjustment effect on the morphology. Various controlling factors affecting the synergistic removal of NO and VOCs were evaluated. It was observed that the presence of VOCs in flue gas has weak impact on NO removal, except for the waste incineration using the Cu@VWTi catalyst. However, a high initial NO concentration had an adverse effect on VOCs removal. Impressively, the optimized copper-doped catalyst (5wt% Cu loaded of smelting plant and coal-fired power plant used catalyst) exhibited excellent performance for p-CT, toluene and DCM removal of 95.0%, 99.6% and 100% at 300 °C, respectively. The toluene and p-CT conversion efficiencies were highest over the catalyst used in the smelting plant after Cu loading, surpassing the benzene conversion efficiency. Cu@VWTi demonstrated excellent performance for p-CT, toluene, and DCM removal at 250 °C. Although 5wt% Cu loading on the catalysts significantly enhanced the stability and anti-jamming of VOCs removal, as well as their tolerance to both SO2 and water vapor. The enhanced mechanism of Cu decoration attributed to the enhanced intensity of acid sites and the stable relative proportion of Oads/Olatt species in the used 5% Cu loaded catalyst due to the redox cycles of Cu and V species. Compared with Brønsted acid, which primarily adsorbs NH4+, Lewis acid mainly adsorbs gas phase acid and forms coordinated NH3 in gas phase. The bonding between toluene and the Cu site was enhanced with an adsorption energy of -130.9 kJ·mol-1, as well as the cracking adsorption of the CH2Cl2 on the Ti site with a bonding energy of -436.7 kJ·mol-1, both indicating strong chemical adsorption. The first step of dechlorination and demethylation was thermodynamically and kinetically favorable for DCM and toluene decomposition.

The realization of beam self-cleaning in a cavity is more challenging than in the outside cavity. The peak power of intracavity pulses needs to be high to reach the threshold of beam self-cleaning, which usually relies on additional diffraction grating to compress pulses in a positive-dispersion cavity. Here, it is first experimentally and numerically demonstrated that self-cleaning can be observed in an all-fiber high peak-power Er-doped spatiotemporal mode-locked (STML) laser at all-negative-dispersion. Through the nonlinear compression of graded-index multimode fiber, the pulses are compressed along with the emergence of beam self-cleaning. Besides, the inherent disorder of multimode fiber accelerates the self-cleaning process. The intracavity pulse energy of approximate to 13 nJ with a pulse duration of 734.5 fs is derived under a highly multimode excitation, with an output pulse energy of 2.33 nJ. The pulse energy is a nearly fourfold improvement over the previous report in all-fiber STML at 1.5 mu m Temporal-dependent characteristics and nonlinear polarization dynamics of beam self-cleaning are also experimentally uncovered. It is demonstrated that the STML fiber laser will enable new insights into nonlinear pulse propagation in cavities and related applications.

Commercial VW/Ti catalyst used in selective catalytic reduction (SCR) process is one of the major sources of SO3 in coal-fired boiler, and modification of VW/Ti catalyst by adding catalytic promoter has been demonstrated to be an effective way to inhibit SO3 generation. In this study, the effect of P addition on the activity of NOx conversion and SO2 oxidation over VW/Ti catalyst was investigated. The results showed that the P-modified VW/Ti catalyst not only enhanced the catalytic activity at low temperature, but also reduced the oxidation rate of SO2. The 1.5PVW/Ti catalyst exhibited the lowest SO2 oxidation rate at 360 degrees C and achieved about 30 % reduction in SO2 oxidation rate when compared to 0PVW/Ti catalyst, whereas the conversion of NOx was still above 95 %. The physicochemical properties of catalysts were comprehensively characterized with N-2 adsorption, XRD, H-2-TPR, NH3-TPD, XPS and DRIFTS. The results illustrated that the W-O-W structure was also the main reason for SO2 oxidation on P-modified VW/Ti catalyst, which oxidized SO2 to form intermediate products HSO4- and constantly replenished in the presence of O-2. The oxidation of SO2 was weakened by the generation of VOPO4 on P-modified VW/Ti catalyst surface, which inhibited the formation of VOSO4 by reducing the adsorption of SO2 on the catalyst. In addition, the release of P-OH and W=O were promoted with the addition of P, which led to a significant increase in the intensity of the Bronsted and Lewis acid sites, resulting in the increase in the conversion of NOx at low temperatures.

By amplifying the cascaded random Raman fiber laser (RRFL) oscillator and ytterbium fiber laser oscillator, we present the first, to the best of our knowledge, demonstration of a 10-kW-level high-spectral-purity all-fiber ytterbium-Raman fiber amplifier (Yb-RFA). With a carefully designed backward-pumped RRFL oscillator structure, the parasitic oscillation between the cascaded seeds is avoided. Leveraging the RRFL with full-open-cavity as the Raman seed, the Yb-RFA realizes 10.7-kW Raman lasing at 1125 nm, which is beyond the operating wavelengths of all the reflection components used in the system. The spectral purity of the Raman lasing reaches 94.7% and the 3-dB bandwidth is 3.9 nm. This work paves a way to combine the temporal stability of the RRFL seed and the power scaling of Yb-RFA, enabling the wavelength extension of high-power fiber lasers with high spectral purity.

以3种品质的废SCR脱硝催化剂粉料M1、M2和M3为原料,与原生钛钨粉M0掺加制备了不同质量掺比的脱硝催化剂,分别对其初始脱硝性能和在实际烟气中运行16000h后的脱硝性能进行跟踪检测评价.实验结果表明,在相同质量掺加比时,掺加废催化剂粉料M1和M2的新催化剂初始性能比未掺加废催化剂粉料M0-0性能降低约30%以上,且运行16000h后的活性劣化速率明显偏快.废催化剂粉料掺加比例越高,负面影响越大.废催化剂的资源化回用应使用高品质粉料,且需严格控制其掺加比.借助激光粒度仪、表面酸量吸附仪(NH3-TPD)以及X射线荧光光谱仪(XRF)等对废催化剂粉料和所制备的催化剂进行了理化分析,废催化剂粉料微观特性无法完全恢复,杂质含量高,是造成新制备催化剂脱硝性能不佳及使用中活性劣化速率快的主要原因.要实现废催化剂粉料大比例用于新催化剂制备,需进一步提高废催化剂粉料的粒径、微观孔隙、表面酸性及降低杂质含量.

In this article, a thorough model of linearly polarized fiber laser considering polarization coupling, mode coupling, SBS, and SRS effects is established. The output results of direct pumping and tandem pumping linearly polarized fiber laser under different SBS and SRS intensity settings are simulated. The results show that direct pumping is a better pumping scheme at present, and if the doping concentration of gain fiber can be further increased and the mode field quality of corresponding passive fiber can be optimized, the disadvantages of tandem pumping can be suppressed. To explore the potential of tandem pumping, a backward tandem pumped linearly polarized fiber amplifier is built and 875 W over 13 dB linearly polarized laser output is obtained.