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Strong second-harmonic generation (SHG) and a wide band gap are two crucial but often conflicting parameters that must be optimized for practical nonlinear optical (NLO) materials. We report herein the first d0-transition-metal (TM) tellurite with half of the d0-TM-octahedra partially fluorinated, namely, quinary RbTeMo2O8F, which exhibits giant SHG responses (27 times that of KH2PO4 (KDP) and 2.2 times that of KTiOPO4 (KTP) with 1064 and 2100 nm laser radiation, respectively), the largest SHG values among all reported metal tellurites. RbTeMo2O8F also possesses a large band gap (3.63 eV), a wide optical transparency window (0.34-5.40 μm), and a significant birefringence (Δn = 0.263 at 546 nm). Theoretical calculations and crystal structure analysis demonstrate that the outstanding SHG responses can be definitively attributed to the uniform alignment of the polarized [MoO5F]/[MoO6] octahedra and the seesaw-like [TeO4], and the consequent favorable summative polarization of the three distinct SHG-active polyhedra, both induced by partial fluorine substitution on the [MoO6] octahedra.

Stereochemically active lone-pair (SCALP) cations are one attractive type of nonlinear optical (NLO)-active units because of their large microcosmic polarizability and anisotropy. Currently, the single and/or dual lone-pair cation-based noncentrosymmetric (NCS) oxides have been extensively investigated and verified to be one class of outstanding NLO materials. From the perspective of function optimization, the integration of three kinds of SCALP cations into one crystal may synergistically improve the NLO properties, which is greatly expected but unexplored to date. Herein, by introducing flexible metal halide bonds to guarantee the stereochemical activity and overcome the energetically favorable antiparallel arrangements of lone-pair cations, the first type of three lone-pair-cation (Pb

In this work, the oxidation state of Sn and Cu active sites for CO

The antimony trisulfide (Sb

A double holmium-silver sulfate was obtained for the first time. The temperature intervals for the formation and stability of the compound were determined by differential scanning calorimetry. The crystal structure of AgHo(SO4)2 was determined by Rietveld method. The X-ray diffraction (XRD) analysis showed that the compound crystallizes in the monoclinic syngony, space group P21/m, with the unit cell parameters a = 4.71751 (4) A, b = 6.84940 (6) A and c = 9.89528 (9) A, β = 95.1466 (4)°, V = 318.448 (5) A3, Z = 2, RB = 1.55 %, T = 303 K. Two types of sulfate tetrahedra were found in the structure, which significantly affected the spectral properties in the infrared range. In the temperature range of 143−703 K, a negative thermal expansion along the b direction accompanied by a positive thermal expansion along the a and c directions was observed. It was established that negative thermal expansion is the result of the deformation of sulfate tetrahedra, which is affected by the movement of holmium and silver atoms. The excitation in the blue spectral range (457.9 nm) produces a luminescence in light blue (489 nm), green (545 nm) and red (654 nm) spectral ranges, and the latter two were of comparable intensity that is favorable for WLED sources. The observed luminescent band distribution is ascribed to the specific crystal field at Ho3+ ion sites rather than a variation of radiationless probability.

This research was financially supported by the NationalNatural Science Foundation of China (nos. 51432006,52002276), the Ministry of Education of China for theChangjiang Innovation Research Team (no. IRT14R23), theInnovation Program of Shanghai Municipal Education Com-mission, and the Ministry of Education and the StateAdministration of Foreign Experts Affairs for the 111 Project(no. B13025). M.G.H. thanks the Australian Research Coun-cil for support (DP170100411).

On the basis of density functional theory calculations, we explored the catalytic properties of various heteroatom-doped black and gray arsenene toward the oxygen reduction reaction (ORR), the oxygen evolution reaction (OER), and the hydrogen evolution reaction (HER). The calculation results show that pristine black (b-As) and gray arsenene (g-As) exhibit poor catalytic performance because of too weak intermediate adsorption. Heteroatom doping plays a key role in optimizing catalytic performance. Among the candidate dopants O, C, P, S, and Sb, O is the most promising one used in arsenene to improve the ORR and OER catalytic performance. Embedding O atoms could widely tune the binding strength of reactive intermediates and improve the catalytic activity. Single O-doped g-AsO1 can achieve efficient bifunctional activity for both the OER and the ORR with optimal potential gap. b-AsO1 and b-AsO2 exhibit the optimal OER and ORR catalytic performance, respectively. For the HER, double C-doped g-AsC2 could tune the adsorption of hydrogen to an optimal value and significantly enhance the catalytic performance. These findings indicate that arsenene could provide a new platform to explore high-efficiency electrocatalysts.

This research was financially supported by the National Natural Science Foundation of China (No. 51432006), the Ministry of Education of China for the Changjiang Innovation Research Team (No. IRT14R23), the Ministry of Education and the State Administration of Foreign Experts Affairs for the 111 Project (No. B13025), and the Innovation Program of Shanghai Municipal Education Commission. M.G.H. and C.Z. thank the Australian Research Council for support (DP170100411).

Materials capable of generating coherent short-wave (

Electrochemical reduction of carbon dioxide (CO2) opens up possibilities toward the formation of value-added products, while CO2 reduction performance remains largely restricted in view of low ener...

The first alkali–metal selenate nonlinear optical (NLO) crystal, Na5(SeO4)(HSeO4)3(H2O)2, has been obtained by in situ hydrothermal synthesis. It crystallizes in the polar and noncentrosymmetric (NCS) space group Cc (no. 9). The structure of Na5(SeO4)(HSeO4)3(H2O)2 can be described as isolated [SeO4]/[HSeO4] tetrahedra connected by H-bonding interactions and Na–O bonds, forming a three-dimensional framework. Powder second-harmonic generation (SHG) measurements show that Na5(SeO4)(HSeO4)3(H2O)2 is phase-matching with a moderate SHG response of ca. 1.6 times that of benchmark KH2PO4. The UV-Vis-NIR spectrum shows that the title compound is a wide-band semiconductor with an optical band gap of 3.57 eV. The birefringence of Na5(SeO4)(HSeO4)3(H2O)2 was calculated to be 0.037 at 1064 nm. First-principles studies show that the [SeO4]/[HSeO4] tetrahedra are the main contributors to its NLO properties. This study indicates that pure selenate is a promising material system to afford NCS structures with SHG responses.

Ultraviolet (UV) nonlinear optical (NLO) materials possess important practical applications in modern laser science and technology, which are attracting significant research interest in the fields of chemistry, physics and materials science. A fluorinated mixed main-group metal sulfate and its defluorinated analogue, Rb2InF3(SO4) (RIFSO) and Rb3In(SO4)3 (RISO), were designed and synthesized for NLO study via mild hydrothermal methods. RIFSO unfortunately crystallizes in centric space group Pbcn (no. 60) while RISO crystallizes in acentric space group R3c (no. 161). Both of them exhibit a one-dimensional chain structure composed of corner-shared [InO2F4] or [InO6] and [SO4] groups. Optical property studies reveal that RISO displays a large band gap (5.75 eV) corresponding to a short UV cut-off edge (215 nm), a moderate second harmonic generation (SHG) efficiency of ∼0.5 times that of KH2PO4 (KDP) with phase-matchable performance, and high thermostability (>800 °C), demonstrating its potential as an applicable UV NLO material. First-principles calculations have been performed to further elucidate the structure–property relationship of RISO.

Rotating speed fluctuation is a key problem that affects the fault diagnosis performance of mechanical equipment. Deep learning theory can use deep neural networks to realize automatic feature extraction and classification, but the existing methods always have defects in computational efficiency and diagnosis error on dealing with this problem. In this paper, combined with the advantages of deep learning, an intelligent fault diagnosis method is proposed to deal with the speed fluctuation problem. Firstly, sparse filtering is employed as a basic framework to construct the deep neural networks for feature extraction. Then, batch normalization is added to each layer to solve the frequency shift and amplitude variation properties of speed fluctuation signals. Finally, softmax regression is used as a classifier in the last layer of the deep neural networks. Two specially designed roller bearing experiments under speed fluctuation condition are adopted to verify the effectiveness of the proposed batch normalized deep sparse filtering method. The results show that the proposed method can completely ignore the influence of speed fluctuation and achieve accurate identification of different fault types, and obtain a higher accuracy than other methods.

The first fluorinated lead vanadate selenite Pb2(V2O4F)(VO2)(SeO3)3 (PVOFS) was successfully synthesized via a mild hydrothermal method. This compound crystallizes in the chiral space group P212121 of the orthorhombic system and it is the first noncentrosymmetric structure in the PbII–VV–SeIV–O–F system. PVOFS is composed of five kinds of second-order Jahn–Teller susceptible asymmetric motifs, including three distinct types of vanadium-centered polyhedral units ([VO5F], [VO6] and [VO5]), [SeO3] pyramids and Pb2+ cations. It features a unique three-dimensional open framework structure displaying three types of tunnels (10-, 8- and 7-membered rings), which enriches the structural diversity for fluorinated vanadate selenite systems. Optical property studies revealed that PVOFS shows a second-harmonic generation response of 0.3 times that of the commercial KH2PO4 with phase matching behavior, a wide transparent region covering IR windows, an optical band gap of 2.35 eV, a high laser damage threshold of 61 times that of AgGaS2, and a large birefringence of 0.105 at 1064 nm. Theoretical calculations have been performed to clarify the correlation between the molecular structure and the optical properties of PVOFS.

Under cold pressure sp

The development of nonlinear optical (NLO) materials has been hindered by competing microstructure requirements: the need to simultaneously engineer a large hyperpolarizability (a large second-harmonic generation (SHG)) and a wide HOMO-LUMO gap (a wide band gap). Herein, a non-centrosymmetric transition-metal (TM) oxyfluoride K

The biogeochemistry of iron (Fe) could affect arsenic (As) fate and change its availability. Fe(II) oxidation mediated by Fe oxidizing bacteria (FeOB) has the potential for As contamination remediation due to the formation of biogenic minerals. However, microbial Fe(II) oxidation coupled with the immobilization of As and the effect of FeOB on As remediation in soils has not been thoroughly investigated. In this study, a FeOB was isolated from a paddy soil and identified as Ochrobactrum sp. EEELCW01. The kinetics reactions were used to investigate how biological and chemical reactions were involved in the Fe(II)‐NO₃⁻‐FeOB system. Microbial Fe(II) oxidation coupled As mineralization, as well as its application in As contaminated paddy soils was studied. The results suggested that biological pathway contributed to the Fe(II) oxidation and NO₃⁻ reduction in the whole process, in which the chemical Fe(II) oxidation by biogenic NO₂⁻ was involved. Meanwhile, Fe(II) facilitated the reduction of NO₂⁻ while inhibited the reduction of NO₃⁻. Adding 2% or more bacteria led to a significant removal effect for aqueous As, resulting in the formation of lepidocrocite and two As‐containing minerals (angelellite, loellingite). With the simultaneous application of FeOB and NO₃⁻, the available As content in soils decreased by 37.6% and stabilized at 0.80 mg kg⁻¹ finally. In addition, the immobilization showed long‐term effect compared to the treatment with Fe(II) or NO₃⁻ alone. The study proved that the isolated FeOB had a significant ability for As mineralization and immobilization, which provided theoretical and application basis for the remediation of As contaminated soils.

This research was financially supported by the National Natural Science Foundation of China (no. 51432006), the Ministry of Education of China for the Changjiang Innovation Research Team (no. IRT14R23), the Ministry of Education and the State Administration of Foreign Experts Affairs for the 111 Project (no. B13025), and the Innovation Program of Shanghai Municipal Education Commission. C.W. thanks the National and Shanghai Postdoctoral Program for Innovative Talents (nos. BX201800216 and 2018192). M.G.H. thanks the Australian Research Council for support (DP170100411).

Variational mode decomposition has been widely applied to machinery fault diagnosis during these years. However, it remains difficult to set proper hyperparameters for the variational mode decomposition, including number of decomposed modes, initial center frequencies, and balance parameter. Moreover, the low efficiency of the existing variational mode decomposition methods hinders their applications to practical diagnostic task. This article proposes an adaptive and efficient variational mode decomposition method after thoroughly investigating its convergence property characteristic. A convergent tendency phenomenon is discovered and is explained mathematically for the first time. Motivated by the convergent tendency phenomenon, the proposed method rapidly and adaptively determines the number and the optimal initial center frequencies of signal latent modes with the guidance of the convergent tendencies of the initial center frequencies changing from small to large. In the proposed method, the number of decomposed modes and initial center frequencies are not hyperparameters that require to be set in advance any more, but are parameters learned from the analyzed signals. The determined parameters enable efficient extraction of the main latent modes contained in the analyzed signals. Therefore, the proposed variational mode decomposition method represents a major improvement in parameter adaption and decomposition efficiency over the existing variational mode decomposition methods. In the application for bearing fault diagnosis, the faulty modes are selected adaptively and the corresponding balance parameters are further optimized efficiently. Two experimental cases validate the proposed method and its superiority over the existing variational mode decomposition methods and the classical fast spectral kurtosis in bearing fault diagnosis.

Birefringent materials with strong optical anisotropy are indispensable for optoelectronic devices as polarizers, isolators, and beam splitters, etc. Here, a new ionic cocrystal KBr·H3C3N3O3 (I) wa...

Anomalous mechanical materials, with counterintuitive stress-strain responding behaviors, have emerged as novel type of functional materials with highly enhanced performances. Here we demonstrate that the materials with coexisting negative, zero and positive linear compressibilities can squeeze three-dimensional volume compressibility into one dimension, and provide a general and effective way to precisely stabilize the transmission processes under high pressure. We propose a “corrugated-graphite-like” structural model and discover lithium metaborate (LiBO2) to be the first material with such a mechanical behavior. The capability to keep the flux density stability under pressure in LiBO2 is at least two orders higher than that in conventional materials. Our study opens a way to the design and search of ultrastable transmission materials under extreme conditions., Anomalous mechanical behaviors provide an opportunity to regulate the functions of materials. Here the authors show that materials with coexisting negative, zero and positive compressibilities can “squeeze” volume compressibility into one direction, and thus stabilize transmission processes under pressure.

Nonlinear optical (NLO) materials have critically important applications in advanced laser technologies. However, achieving a good balance between the mutual competing NLO properties and band gap w...

9 pags., 3 figs., 3 tabs., The presence of extremely large negative linear compressibilities (NLC) in crystalline silver oxalate was discovered in a recent work by using first principles solid-state calculations. Although the minimum value of the NLC was found for a negative applied hydrostatic pressure, in this work the presence of NLC in this material for positive applied pressures is verified experimentally by means of high-pressure X-ray diffraction experiments performed at room temperature in the Beijing synchrotron radiation facility. The results of this study demonstrate with certainty that the compressibility of silver oxalate along [010] crystallographic direction is negative for applied pressures in the range from 0.0 to 0.85 GPa. Since the measured compressibility decreases largely as the pressure decreases, large negative values of the compressibility are expected for negative applied pressures in agreement with the results found using first principles methods. Furthermore, the analysis of the variation of the lattice parameters of the crystal structure of silver oxalate under pressure in the principal axes reference system revealed that this material also exhibits the largest negative area compressibility phenomenon found so far at zero pressure, the values of the compressibilities along two of the principal axes being − 16.7 and − 20.0 TPa−1. The negative compressibility phenomenon in silver oxalate can be rationalized in terms of a “chains of rotating parallelograms” structural model., This work was supported by the National Scientific Foundations of China (Grants 51702330, 51872297 and 11974360).

Zero thermal expansion (ZTE) materials, keeping size constant as temperature varies, are valuable for resisting the deterioration of the performance from environmental temperature fluctuation, but ...

An ultraviolet nonlinear optical (NLO) crystal La2SrB10O19 (LSB) has been firstly grown through the spontaneous crystallization using SrO-Li2O-B2O3-MoO3 flux. LSB crystallizes in noncentrosymmetric...

Intelligent fault diagnosis is an effective method to guarantee the continuous and efficient operation of rotating machinery. Compared with the experimental environment, noise is inevitable in real word industrial applications, which causes serious degradation of the performance of intelligent fault diagnosis methods. In view of this, this study aims to provide a method that could accurately diagnose faults under noisy environment. In this paper, we firstly discuss the characteristics of normalization and the feature extracting process of sparse filtering. Then, we propose a novel method based on the L3/2-norm, Hankel-training matrix, normalized weight matrix and feature normalization for rotating machinery fault diagnosis under noisy environment. The proposed method is applied to the fault diagnosis of rolling bearing and planetary gearbox with noise interference. The verification results confirm that the proposed method is a promising tool that shows strong noise adaptability using the training of original datasets without any time-consuming denoising preprocessing.

Bearing fault diagnosis is critical for rotating machinery condition monitoring since it is a key component of rotating machines. One of the challenges for bearing fault diagnosis is to accurately realize fault feature extraction from original vibration signals. To tackle this problem, the novel group sparsity signal decomposition method is proposed in this article. For the sparsity within and across groups’ property of the bearing vibration signals, the nonconvex group separable penalty is introduced to construct the objective function, leading to that the noise between the adjacent impulses can be eliminated and the impulses can be effectively extracted. Furthermore, since the penalty function is nonconvex, the convexity condition of the corresponding objective function to the global minimum is discussed. In addition, to improve the efficiency of parameter selection, this article presents an adaptive regularization parameter selection strategy. Simulation and experimental studies show that compared with the traditional method, the proposed method can better preserve the target components and reducing uncorrelated interference components for bearing fault diagnosis.

Combining a wide band gap, strong second-harmonic generation (SHG), and good phase matchability into a single structure is an ongoing challenge in the design of nonlinear optical (NLO) materials. H...

In multitrain subway systems, excessive rail potential and stray current (RP-SC) appear in the reflux system during the dynamic operations of an over voltage protection device (OVPD) and a drainage device (DD), which has not been clarified until now and has seriously affected the safe operation of the systems. To accurately evaluate RP-SC with dynamic traction networks, the equivalent method of the reflux system with mixed parameters is proposed, based on which a new simulation model that considers the dynamic characteristics of OVPD and DD is established. The control characteristics of OVPD and DD are analyzed in the established simulation model with multiple trains operating in the dynamic traction network. Dynamic RP-SC are simulated in different cases and are validated in the field tests at Guangzhou Metro Line 2. Results show that the RP-SC with dynamic traction networks can be effectively evaluated by the proposed model. RP-SC are greatly influenced by the dynamic operations of OVPD and DD, and excessive RP-SC can be mitigated by adjusting the grounding resistances of the closed OVPD.

Structural modulations have been recently found to cause some unusual physical properties, such as superconductivity or charge density waves; however, thus-induced nonlinear optical properties are rare. We report herein two unprecedented incommensurately modulated nonlinear optical sulfides exhibiting phase matching behavior, A2 SnS5 (A=Ba, Sr), with the (3+1)D superspace groups P21 21 2(00γ)00s or P21 (α0γ)0, featuring different modulations of the [Sn2 S7 ]∞ belts. Remarkably, Ba2 SnS5 exhibits an excellent second harmonic generation (SHG) of 1.1 times that of the benchmark compound AgGaS2 at 1570 nm and a very large laser-induced damage threshold (LIDT) of 8×AgGaS2 . Theoretical studies revealed that the structural modulations increase the distortions of the Sn/S building units by about 44 or 25 % in A2 SnS5 (A=Ba, Sr), respectively, and enhance significantly the SHG compared with α-Ba2 SnSe5 without modulation. Besides, despite the smaller Eg , the A2 SnS5 samples exhibit higher LIDTs owing to their smaller thermal expansion anisotropies (Ba2 SnS5 (1.51)

Rational doping and compositional control remain significant challenges in designing luminescent metal halides to achieve highly efficient and tunable emission. Here, the air-stable lead-free Cs2In...

Normal operation of bearing is the key to ensure the reliability and security of rotary machinery, so that bearing fault diagnosis is quite significant. However, the large amount of data collected by modern data acquisition system and time-varying working conditions make it hard to diagnose the fault using traditional methods To break the predicaments, we propose a new intelligent fault diagnosis framework inspired by the infinitesimal method. The proposed model including three parts can ignore the effect of different rotational speeds. Firstly, the sample is segmented and every segment dimension is extended by input network to ensure the adequate information memory space. Secondly, the classification information is stored and transferred in the long short-term memory (LSTM) network and output to the third part. In this process, the working condition information is ignored because of the gate units function. Finally, the likelihood is given by output network to classify the health conditions. Besides, we propose a loss function combining all the output of every time step and employ dropout to train the model, which increase the training efficiency and diagnosis ability. The bearing datasets under time-varying speeds and loads are used to verify the proposed method. The application result shows that our method has higher accuracy with simpler structure, and is superior to the traditional method in bearing fault diagnosis. Moreover, we give a physical interpretation of the proposed model.

The first alkali metal rare earth iodate fluoride, Li2Ce(IO3)4F2, was synthesized using hydrothermal method. This compound features a novel [CeI4O12F2]∞ infinite layer with each [CeO6F2] dodecahedr...

This article describes a fast and simple electrochemical assay for detecting cell concentration. After cell death, the membrane of cells will be broken, and DNA molecules contained in the cells will be released, but this does not happen in living cells. Sodium molybdate can react with the phosphate backbone of the released DNA molecules to form phosphomolybdate precipitation and produces a corresponding redox current. The higher the concentration of DNA, the stronger the intensity of the current generated. Sodium molybdate solution and centrifuged cell supernatant were added onto the glassy carbon electrode to determine the cell concentration by measuring the current intensity. The cell viability, which means the ratio of living cells to the total cells, can also be determined by this method. This assay has the advantages of high sensitivity, low detection limit, and wide detection range. In addition, this method was successfully applied to the detection of cell concentration in human serum, which has potential clinical applications.

Deep learning technology has been gradually applied to solve a variety of fault diagnosis problems because of its outstanding feature learning and nonlinear classification abilities. However, few deep learning network models can be applied to both variable speed conditions and unbalanced samples scenarios in fault diagnosis, especially in extreme cases where fault samples are missing. And most of the fault diagnosis models do not have the ability to update automatically as the collected fault data increases. To deal with the above problems, a deep learning model named renewable fusion fault diagnosis network (RFFDN) is proposed. The network has three main parts: improved feature classification network; second order statistics fusion network and unbalanced feature comparison network. Moreover, these three networks are simultaneously organized on a two-branch convolutional neural network (CNN) architecture with fused data input, so as to facilitate the network to learn the depth nonlinear domain invariant features. Finally, the RFFDN model and other mainstream fault diagnosis models are tested on two different datasets. The results show that the RFFDN model not simply achieves high diagnostic accuracy in diagnosis results, but also extracts the domain invariant features at variable speed conditions under unbalanced samples, and accurately classifies the new faults. These prove that the model can not only be applied to a variety of operating modes, but can be updated as more data are collected as well, which is of great significance to the field of fault diagnosis.

Currently, study on the relevant methods of variational mode decomposition (VMD) is mainly focused on the selection of the number of decomposed modes and the bandwidth parameter using various optimization algorithms. Most of these methods utilize the genetic-like algorithms to quantitatively analyze these parameters, which increase the additional initial parameters and inevitably the computational burden due to ignoring the inherent characteristics of the VMD. From the perspective to locate the initial center frequency (ICF) during the VMD decomposition process, we propose an enhanced VMD with the guidance of envelope negentropy spectrum for bearing fault diagnosis, thus effectively avoiding the drawbacks of the current VMD-based algorithms. First, the ICF is coarsely located by envelope negentropy spectrum (ENS) and the fault-related modes are fast extracted by incorporating the ICF into the VMD. Then, the fault-related modes are adaptively optimized by adjusting the bandwidth parameters. Lastly, in order to identify fault-related features, the Hilbert envelope demodulation technique is used to analyze the optimal mode obtained by the proposed method. Analysis results of simulated and experimental data indicate that the proposed method is effective to extract the weak faulty characteristics of bearings and has advantage over some advanced methods. Moreover, a discussion on the extension of the proposed method is put forward to identify multicomponents for broadening its applied scope.

La/Ce0.5Mn0.5 catalysts prepared by wetness impregnation of Ce0.5Mn0.5 with La(NO3)3 (aq) were used in catalytic oxidation of ethyl acetate. Characterization by X-ray diffractometer (XRD), H2 temperature programmed reduction (H2-TPR), X-ray photoelectron spectroscopy (XPS) and Raman shows that La/Ce0.5Mn0.5 catalysts have fluorite-like structure. La/Ce0.5Mn0.5 catalyst presents high activity with T90 (the temperature needed for 90% conversion) of 200 °C, where ethyl acetate is almost completely converted into CO2. The conversion at 195 °C maintains at 80% for at least 100 h. The intermediates were mainly ethanol and acetaldehyde whose amounts are below 250 × 10–6 and 16 × 10–6, respectively. In situ FTIR indicates that the modes of dissociative adsorption of ethyl acetate are related to surface oxygen species, which affect the stability of catalysts and the selectivity for ethanol and acetaldehyde intermediates.

In this paper, we have experimentally demonstrated a secure 100 Gb/s intensity-modulation and direct-detection transmission over 100 km standard single-mode fiber (SSMF) based on quantum noise stream cipher (QNSC) for the first time. The original 4-level pulse-amplitude modulation (PAM4) data is mapped to M-level data sequence randomly, and quantum noise such as the generated amplified spontaneous emission noise and the shot noise in the channel can mask these adjacent signal levels. The legitimate receiver needs to distinguish not M-level encrypted data but 4-level data with the shared key. In our scheme, a calculated detection failure probability of 98.72% is achieved. Apparently, more quantum noise contributes to higher security but the worse signal to noise ratio. To balance algorithm complexity, transmission performance and security performance, a sparse $\ell _{1} $ regularization based on recursive least square (RLS) algorithm is proposed and firstly used in Volterra equalizer. To eliminate the power fading induced by fiber dispersion, a dual-drive Mach-Zehnder modulator is used to achieve single-sideband modulation, and no dispersion compensation is required. By these means, 100 Gb/s PAM4-QNSC signal transmission over 100 km SSMF with the bit error rate (BER) below the 7% overhead hard-decision forward error correction threshold of $3.8 \times 10^{-3}$ is achieved, and > 59% complexity reduction of Volterra equalizer is realized. Moreover, the measured BER of 150 Gb/s PAM8-QNSC signal transmission over 50 km SSMF could go below the 20% overhead soft-decision forward error correction threshold of $2.0\times 10^{-2}$ . The results validate that the proposed scheme is effective to realize low-cost, high-speed (> 100 Gb/s), and secure optical fiber transmission in the data center.

Efficient broadband emission related to self-trapped excitons (STEs) in low-dimensional perovskites and double perovskite crystals has attracted great attention due to its potential applications in optoelectronics. However, the formation of STEs in three-dimensional (3D) all-inorganic perovskites (CsPbX3) is difficult. Here, through the doping of ytterbium (Yb3+) or erbium (Er3+) ions into CsPbX3 crystals, we observed broadband luminescence from STEs with a linewidth exceeding 200 nm and a Stokes shift of ∼1 eV. Theoretical concepts and experimental studies demonstrated that Pb2+ in perovskites could be replaced by impure ions. Also, the Pb2+ substitution defects and adjacent halide vacancies introduced defect states lying just below the conduction band minimum of perovskites. Strong electron–phonon coupling between trapped carriers and deformation of the [PbX6] cage reduced the energy gap of perovskites. Our study sheds new light on the permanent defects induced in extrinsic STEs in 3D inorganic perovskites. It also provides a clear microscopic picture of the underlying mechanism of formation of STEs.