Defocus-integration interferometric scattering microscopy for speckle suppression and enhancing nanoparticle detection on a substrate.

Direct optical detection and imaging of single nanoparticles on a substrate in wide field underpin vast applications across different research fields. However, speckles originating from the unavoidable random surface undulations of the substrate ultimately limit the size of the decipherable nanoparticles by the current optical techniques, including the ultrasensitive interferometric scattering microscopy (iSCAT). Here, we report a defocus-integration iSCAT to suppress the speckle noise and to enhance the detection and imaging of single nanoparticles on an ultra-flat glass substrate and a silicon wafer. In particular, we discover distinct symmetry properties of the scattering phase between the nanoparticle and the surface undulations that cause the speckles. Consequently, we develop the defocus-integration technique to suppress the speckles. We experimentally achieve an enhancement of the signal-to-noise ratio by 6.9 dB for the nanoparticle detection. We demonstrate that the technique is generally applicable for nanoparticles of various materials and for both low and high refractive index substrates.

Intake of compound probiotics accelerates the construction of immune function and gut microbiome in Holstein calves.

Acquired immunity is an important way to construct the intestinal immune barrier in mammals, which is almost dependent on suckling. To develop a new strategy for accelerating the construction of gut microbiome, newborn Holstein calves were continuously fed with 40 mL of compound probiotics (containing Lactobacillus plantarum T-14, Enterococcus faecium T-11, Saccharomyces cerevisiae T-209, and Bacillus licheniformis T-231) per day for 60 days. Through diarrhea rate monitoring, immune index testing, antioxidant capacity detection, and metagenome sequencing, the changes in diarrhea incidence, average daily gain, immune index, and gut microbiome of newborn calves within 60 days were investigated. Results indicated that feeding the compound probiotics reduced the average diarrhea rate of calves by 42.90%, increased the average daily gain by 43.40%, raised the antioxidant indexes of catalase, superoxide dismutase, total antioxidant capacity, and Glutathione peroxidase by 22.81%, 6.49%, 8.33%, and 13.67%, respectively, and increased the immune indexes of IgA, IgG, and IgM by 10.44%, 4.85%, and 6.12%, respectively. Moreover, metagenome sequencing data showed that feeding the compound probiotics increased the abundance of beneficial strains (e.g., Lactococcus lactis and Bacillus massionigeriensis) and decreased the abundance of some harmful strains (e.g., Escherichia sp. MOD1-EC5189 and Mycobacterium brisbane) in the gut microbiome of calves, thus contributing to accelerating the construction of healthy gut microbiome in newborn Holstein calves. IMPORTANCE: The unstable gut microbiome and incomplete intestinal function of newborn calves are important factors for the high incidence of early diarrhea. This study presents an effective strategy to improve the overall immunity and gut microbiome in calves and provides new insights into the application of compound probiotics in mammals.

A deep learning fusion network trained with clinical and high-frequency ultrasound images in the multi-classification of skin diseases in comparison with dermatologists: a prospective and multicenter study.

Background: Clinical appearance and high-frequency ultrasound (HFUS) are indispensable for diagnosing skin diseases by providing internal and external information. However, their complex combination brings challenges for primary care physicians and dermatologists. Thus, we developed a deep multimodal fusion network (DMFN) model combining analysis of clinical close-up and HFUS images for binary and multiclass classification in skin diseases. Methods: Between Jan 10, 2017, and Dec 31, 2020, the DMFN model was trained and validated using 1269 close-ups and 11,852 HFUS images from 1351 skin lesions. The monomodal convolutional neural network (CNN) model was trained and validated with the same close-up images for comparison. Subsequently, we did a prospective and multicenter study in China. Both CNN models were tested prospectively on 422 cases from 4 hospitals and compared with the results from human raters (general practitioners, general dermatologists, and dermatologists specialized in HFUS). The performance of binary classification (benign vs. malignant) and multiclass classification (the specific diagnoses of 17 types of skin diseases) measured by the area under the receiver operating characteristic curve (AUC) were evaluated. This study is registered with www.chictr.org.cn (ChiCTR2300074765). Findings: The performance of the DMFN model (AUC, 0.876) was superior to that of the monomodal CNN model (AUC, 0.697) in the binary classification (P = 0.0063), which was also better than that of the general practitioner (AUC, 0.651, P = 0.0025) and general dermatologists (AUC, 0.838; P = 0.0038). By integrating close-up and HFUS images, the DMFN model attained an almost identical performance in comparison to dermatologists (AUC, 0.876 vs. AUC, 0.891; P = 0.0080). For the multiclass classification, the DMFN model (AUC, 0.707) exhibited superior prediction performance compared with general dermatologists (AUC, 0.514; P = 0.0043) and dermatologists specialized in HFUS (AUC, 0.640; P = 0.0083), respectively. Compared to dermatologists specialized in HFUS, the DMFN model showed better or comparable performance in diagnosing 9 of the 17 skin diseases. Interpretation: The DMFN model combining analysis of clinical close-up and HFUS images exhibited satisfactory performance in the binary and multiclass classification compared with the dermatologists. It may be a valuable tool for general dermatologists and primary care providers. Funding: This work was supported in part by the National Natural Science Foundation of China and the Clinical research project of Shanghai Skin Disease Hospital.

Bright Nonblinking Photoluminescence with Blinking Lifetime from a Nanocavity-Coupled Quantum Dot.

Colloidal quantum dots (QDs) are excellent luminescent nanomaterials for many optoelectronic applications. However, photoluminescence blinking has limited their practical use. Coupling QDs to plasmonic nanostructures shows potential in suppressing blinking. However, the underlying mechanism remains unclear and debated, hampering the development of bright nonblinking dots. Here, by deterministically coupling a QD to a plasmonic nanocavity, we clarify the mechanism and demonstrate unprecedented single-QD brightness. In particular, we report for the first time that a blinking QD could obtain nonblinking photoluminescence with a blinking lifetime through coupling to the nanocavity. We show that the plasmon-enhanced radiative decay outcompetes the nonradiative Auger process, enabling similar quantum yields for charged and neutral excitons in the same dot. Meanwhile, we demonstrate a record photon detection rate of 17 MHz from a colloidal QD, indicating an experimental photon generation rate of more than 500 MHz. These findings pave the way for ultrabright nonblinking QDs, benefiting diverse QD-based applications.

Development of composite amine functionalized polyester microspheres for efficient CO2 capture.

In order to reduce the impact of greenhouse gases on the environment, the development of various new CO2 capture materials has become a hot spot. In this work, a novel composite amine solid adsorbent was prepared by simultaneously using tetraethylenepentamine (TEPA) and 2-[2-(dimethylamino) ethoxy] ethanol (DMAEE) for amine functionalization on the polyester microsphere carrier. The introduction of methyl methacrylate (MMA) with high glass transition temperature into the polyester carrier makes the carrier microspheres have high hardness. At the same time, the carrier also contains active epoxy groups and hydrophobic glycidyl methacrylate (GMA, which can undergo ring-opening reaction with composite amines to achieve high-load and low-energy chemical grafting of amines on the carrier. The composite aminated polyester microspheres were used as an efficient adsorbent for CO2 in simulated flue gas. The results show that the synergistic effect of TEPA-DMAEE composite amine system in the adsorbent is beneficial to the improvement of CO2 capture capacity. When the total amine content in the impregnating solution is 45 wt% and the composite amine ratio is TEPA: DMAEE = 6: 4, the CO2 adsorption capacity can reach the optimal value of 2.45 mmol/ g at 70 °C. In addition, the composite amine microsphere adsorbent has cyclic regeneration performance. Importantly, through kinetic fitting, the Avrami kinetic model fits the CO2 adsorption better than the quasi-first-order and quasi-second-order kinetic models, which proves that physical adsorption and chemical adsorption coexist in the adsorption process. This simple, long-term stable and excellent selective separation performance makes amine-functionalized adsorbents have potential application prospects in CO2 capture.

In vivo protein turnover rates in varying oxygen tensions nominate MYBBP1A as a mediator of the hyperoxia response.

Oxygen deprivation and excess are both toxic. Thus, the body's ability to adapt to varying oxygen tensions is critical for survival. While the hypoxia transcriptional response has been well studied, the post-translational effects of oxygen have been underexplored. In this study, we systematically investigate protein turnover rates in mouse heart, lung, and brain under different inhaled oxygen tensions. We find that the lung proteome is the most responsive to varying oxygen tensions. In particular, several extracellular matrix (ECM) proteins are stabilized in the lung under both hypoxia and hyperoxia. Furthermore, we show that complex 1 of the electron transport chain is destabilized in hyperoxia, in accordance with the exacerbation of associated disease models by hyperoxia and rescue by hypoxia. Moreover, we nominate MYBBP1A as a hyperoxia transcriptional regulator, particularly in the context of rRNA homeostasis. Overall, our study highlights the importance of varying oxygen tensions on protein turnover rates and identifies tissue-specific mediators of oxygen-dependent responses.

1200-W all polarization-maintaining fiber GHz-femtosecond-pulse laser with good beam quality.

In this work, we demonstrate a 1200-W average power all polarization-maintaining (PM) fiber ultrafast laser system operating at 1.0 µm. In accordance with the numerical modeling, the PM fiber laser system is designed and it delivers linearly-polarized femtosecond pulses at a 1.39-GHz fundamental repetition rate, with a maximum output power of 1214 W - to the best of our knowledge, the highest average power from all PM fiber ultrafast laser at 1.0 µm to date. The pulse width can be compressed to ∼800 fs with a beam quality of M2 < 1.1. This kilowatt-class all PM fiber laser system is expected to open new potential for high energy pulse generation through temporal coherent combination and laser ablation using GHz burst fs laser.

Continuous Extrusion Forming Technology of Magnesium Alloy Thin-Walled Tubules.

This paper proposes a new technology of superimposed billet extrusion-forming for thin-walled magnesium alloy tubes. This process represents an improvement over the current technology, which suffers from low production efficiency, poor forming accuracy, and low material utilization. We developed a detailed forming process and mold structure, in which the excess material of the front billet is extruded out of the mold as the rear billet pushes on the front one. Through continuous extrusion, online direct water cooling, and cutting, the automated continuous production of thin-walled tubules is achieved. The optimization of the mandrel structure and its hovering action is also included, with the aim of improving the lifespan of the mandrel and the accuracy of tube size. The numerical simulation method evaluates the effect of the die angle (α) on the tube, formed using FORGE NXT 1.1. The results show that for an angle of less than 70°, the defect length of the tube decreases as the die angle decreases, forming an ordered flow of superimposed billets. If the angle is less than 50°, the two adjacently formed tubes separate automatically, with no need for the subsequent cutting process. The best choice of die angle is about 50°, which takes into account the effect of the change in extrusion force.

Genetic-Algorithm-Based Inverse Optimization Identification Method for Hot-Temperature Constitutive Model Parameters of Ti6Al4V Alloy.

A precise constitutive model is the foundation and key to finite element simulation in material volume forming and the optimization of the hot working process. Hence, to build a precise constitutive model, a method based on a genetic algorithm (GA) for the inverse optimization identification of parameters is presented in this paper. The idea of this method is to continuously adjust the model parameters through GA until the objective function reaches the minimum value. In this study, hot compression experiments were performed on the Gleeble-1500D thermal simulator at temperatures ranging from 800 °C to 1000 °C and strain rates of 0.01 s-1 to 1 s-1. The Arrhenius-type (A-T) model considering strain compensation and the Johnson-Cook (JC) model considering the coupling effects of strain, temperature and strain rate were constructed, respectively, by using the regression method and the parameter inverse optimization identification method. For the purposes of comparing and verifying the reliability of the predictions of the two established constitutive models, the correlation coefficient (R), average absolute relative error (AARE), and relative error (RE) were adopted. The results show that both the optimized A-T model and the optimized JC model have high prediction accuracy. Compared to the optimized JC model, the optimized A-T model demonstrated a higher correlation coefficient, by 0.003, and a lower average absolute relative error, by 1.43%. Furthermore, the relative error distribution of the optimized A-T model was found to be more concentrated than that of the optimized JC model. These results suggest that the A-T model is more appropriate than the JC model for characterizing the high-temperature deformation behavior of Ti6Al4V alloy.

An Inverse Optimization Method for the Parameter Determination of the High-Temperature Damage Model and High-Temperature Damage Graph of Ti6Al4V Alloy.

Ti6AL4V alloy is widely used in the biomedical and energy vehicle industries, among others. Ti6Al4V alloy cannot be fabricated at ambient temperatures; hence, it requires hot forming. However, this method is susceptible to crack defects. The crack defect problem of Ti6AL4V alloy in the hot-forming process cannot be ignored, so we must develop a precise hot-forming damage prediction model. In this study, three high-temperature damage models of Ti6Al4V alloy were developed, considering the temperature and strain rate. These models were derived from the normalized Cockcroft and Latham (NCL), Oyane, and Rice and Tracey (RT) damage models. The damage parameters of the models were identified using a genetic algorithm combined with finite element simulation. The force accumulation error of the Ti6AL4V alloy specimen, which was obtained from a simulated thermal tensile test and an actual test, was used as an optimization target function. Then, the damage parameters were optimized using the genetic algorithm until the target function reached the minimum value. Finally, the optimal damage model parameter was obtained. Through program development, the three high-temperature damage models established in this paper were embedded into Forge® NxT 2.1 finite element software. The simulated thermal tensile test of Ti6AL4V alloy was performed at a temperature of 800-1000 °C and a strain rate of 0.01-5 s-1. The simulated and actual fracture displacements of the tensile specimens were compared. The correlation coefficients (R) were calculated, which were 0.997, 0.951, and 0.912. Of the high-temperature damage models, the normalized Cockcroft and Latham high-temperature damage model had higher accuracy in predicting crack defects of Ti6Al4V alloy during the hot-forming process. Finally, a fracture strain graph and a high-temperature damage graph of Ti6Al4V alloy were constructed. The Ti6Al4V alloy damage evolution and thermal formability were analyzed in relation to the temperature and strain rate.

Finite Element Analysis of Dynamic Recrystallization Model and Microstructural Evolution for GCr15 Bearing Steel Warm-Hot Deformation Process.

Warm deformation is a plastic-forming process that differs from traditional cold and hot forming techniques. At the macro level, it can effectively reduce the problem of high deformation resistance in cold deformation and improve the surface decarburization issues during the hot deformation process. Microscopically, it has significant advantages in controlling product structure, refining grain size, and enhancing product mechanical properties. The Gleeble-1500D thermal-mechanical physical simulation system was used to conduct isothermal compression tests on GCr15 bearing steel. The tests were conducted at temperatures of 600-1050 °C and strain rates of 0.01-5 s-1. Based on the experimental data, the critical strain model and dynamic recrystallization model for the warm-hot forming of GCr15 bearing steel were established in this paper. The model accuracy is evaluated using statistical indicators such as the correlation coefficient (R). The dynamic recrystallization model exhibits high predictive accuracy, as indicated by an R-value of 0.986. The established dynamic recrystallization model for GCr15 bearing steel was integrated into the Forge® 3.2 numerical simulation software through secondary program development to simulate the compression process of GCr15 warm-hot forming. The dynamic recrystallization fraction was analyzed in various deformation regions. The grain size of the severe deformation zone, small deformation zone, and difficult deformation zone was compared based on simulated compression specimens under the conditions of 1050 °C and 0.1 s-1 with the corresponding grain size obtained with measurement based on metallographic photos; the relative error between the two is 5.75%. This verifies the accuracy of the established dynamic recrystallization and critical strain models for warm-hot deformation of GCr15 bearing steel. These models provide a theoretical basis for the finite element method analysis and microstructure control of the warm-hot forming process in bearing races.

Interaction between hydrophobic chitosan derivative and asphaltene in heavy oil to reduce viscosity of heavy oil.

The high viscosity of heavy oil made it difficult to exploit and transport heavy oil in pipeline. In this research, N-[(2-hydroxy-3-trimethylammonium) propyl] O-stearoyl chitosan tetraphenylboride (sc-CTS-st) was synthesized from chitosan, 2, 3-epoxy-propyl trimethyl ammonium chloride, sodium tetraphenylboron and stearyl chloride. sc-CTS-st contains long chain saturated aliphatic hydrocarbon, hydroxyl group and benzene ring, which could be dissolved in heavy oil fully and interacted with asphaltene. At 50 °C, the viscosity of heavy oil could be reduced to 13,800 mPa·s at most, with a viscosity reduction rate of 57.54 %. SEM and XRD showed that sc-CTS-st could affect the supramolecular accumulation structure of asphaltenes. Using FT-IR, sc-CTS-st could interact with asphaltene in the form of hydrogen bonds using the polar parts of the molecule, thereby weakening the self-association between asphaltene molecules. Molecular simulation was used to demonstrate the interaction mechanism between chitosan derivatives and asphaltenes. sc-CTS-st interacted with asphaltene through chemical bonding and influenced the self-association of asphaltene molecules. In addition, the non-polar portion of sc-CTS-st molecules could form a coating on the outside of the asphaltenes stacking structure, thus shielding or reducing the polarity of the stacking structure surface.

Tunable resonance Raman scattering of quantum dots in a nonlinear excitation regime.

Controllable tuning of electron-phonon coupling strength and excited state dynamics is important for the understanding of resonance Raman scattering in low-dimensional semiconductors. Here, we report a significant and reversible field-induced modulation in absolute resonance Raman intensity of quantum dots using ionic liquid gating. Meanwhile, a potential-dependent nonlinear relationship is present between Raman intensity and excitation power density. By exploring the parameter space within a time domain model, we find that the Raman intensity variation is mainly determined by the homogeneous linewidth. We further propose that the Fermi level positions and exciton species play key roles in the excited state decay rates.

Effects of long-term no-tillage on the functional potential of microorganisms involved in the nitrogen, phosphorus and sulfur cycles of black soil.

Understanding the effects of different tillage practices on functional microbial abundance and composition in nitrogen (N), phosphorus (P) and sulfur (S) cycles are essential for the sustainable utilization of black soils. Based on an 8-year field experiment located in Changchun, Jilin Province, we analyzed the abundance and composition of N, P and S cycling microorganisms and their driving factors in different depths of black soil under no til-lage (NT) and conventional tillage (CT). Results showed that compared with CT, NT significantly increased soil water content (WC) and microbial biomass carbon (MBC) at soil depth of 0-20 cm. Compared with CT, NT significantly increased the abundances of functional and encoding genes related to N, P and S cycling, including the nosZ gene encoding N2O reductase, the ureC gene performing organic nitrogen ammoniation, the nifH gene encoding nitrogenase ferritin, the functional genes phnK and phoD driving organic phosphorus mineralization, the encoding pyrroloquinoline quinone synthase ppqC gene and the encoding exopolyphosphate esterase ppX gene, and the soxY and yedZ genes driving sulfur oxidation. The results of variation partitioning analysis and redundancy analysis showed that soil basic properties were the main factors affecting the microbial composition of N, P and S cycle functions (the total interpretation rate was 28.1%), and that MBC and WC were the most important drivers of the functional potential of soil microorganisms in N, P and S cycling. Overall, long-term no tillage could increase the abundance of functional genes of soil microorganisms by affecting soil environment. From the perspective of molecular biology, our results elucidated that no tillage could be used as an effective soil management measure to improve soil health and maintain green agricultural development.

Oxygen toxicity causes cyclic damage by destabilizing specific Fe-S cluster-containing protein complexes.

Oxygen is toxic across all three domains of life. Yet, the underlying molecular mechanisms remain largely unknown. Here, we systematically investigate the major cellular pathways affected by excess molecular oxygen. We find that hyperoxia destabilizes a specific subset of Fe-S cluster (ISC)-containing proteins, resulting in impaired diphthamide synthesis, purine metabolism, nucleotide excision repair, and electron transport chain (ETC) function. Our findings translate to primary human lung cells and a mouse model of pulmonary oxygen toxicity. We demonstrate that the ETC is the most vulnerable to damage, resulting in decreased mitochondrial oxygen consumption. This leads to further tissue hyperoxia and cyclic damage of the additional ISC-containing pathways. In support of this model, primary ETC dysfunction in the Ndufs4 KO mouse model causes lung tissue hyperoxia and dramatically increases sensitivity to hyperoxia-mediated ISC damage. This work has important implications for hyperoxia pathologies, including bronchopulmonary dysplasia, ischemia-reperfusion injury, aging, and mitochondrial disorders.

Simulation of the nonlinear Kerr and Raman effect with a parallel local time-stepping DGTD solver.

In this paper, an efficient discontinuous Galerkin time-domain (DGTD) method is proposed to solve Maxwell's equations for nonlinear Kerr or Raman media. Based on our previous work, an arbitrary high-order derivatives DGTD method with a local time-stepping scheme is introduced for simulating dynamic optical responses in nonlinear dispersive media such that the nonlinear effects do not impose constraints on the stability conditions for linear subdomains. Therefore, the scheme enables the simulations in the nonlinear and linear media regions with independent time-stepping increments, which greatly improves the efficiency of the time-domain analysis. Moreover, by applying an iteration solution scheme, the proposed method preserves the intrinsic local features, which is favorable for the realization of highly parallelized algorithms. Numerical examples demonstrate the accuracy and the efficiency of our proposed method. We believe the proposed method provides an effective tool for numerical analysis of nonlinear optical phenomena.

Elevation of hemoglobin A1c increases the risk of decline in left ventricular systolic function among patients with coronary artery disease.

AIMS: The aim of this study was to investigate the association of HbA1c and left ventricular (LV) systolic function among patients with coronary artery disease (CAD). METHODS: CAD patients from the Cardiorenal ImprovemeNt II (CIN-II, NCT05050877) registry were included in the study. They were separated into four groups based on HbA1c levels (Q1: HbA1c<5.7%; Q2: 5.7% ≤ HbA1c < 6.1%; Q3: 6.1% ≤ HbA1c < 6.9%; Q4: HbA1c ≥ 6.9%). The endpoint was decline in LV systolic function, defined as an absolute decrease in LV ejection fraction (LVEF) ≥10% from baseline to follow-up with 3-12 months. The association of HbA1c and LVEF was assessed by logistics regression models. RESULTS: CAD patients (n = 3,994) (age 62.9 ± 10.6 years; 22.2% female) were included in the final analysis. A decline in LV systolic function was recorded in 429 (11%) patients during follow-up. After fully adjusting for confounders, HbA1c was significantly associated with the high risk of decline in LV systolic function (OR 1.12 [95%CI 1.05-1.20] P = 0.001). By stratifying HbA1c as four groups, there is a significantly increased risk of decline in LV systolic function when HbA1c ≥6.1% (Q2, Q3 and Q4 vs Q1, with OR 1.22 [0.88-1.68] P = 0.235; OR 1.48 [1.07-2.05] P = 0.019; OR 1.60 [1.160-2.22] P = 0.004, respectively). Meanwhile, patients with decline in LV systolic function had a higher risk of cardiovascular death. CONCLUSIONS: Elevated HbA1c is a predictor of decline in LV systolic function in CAD patients. Clinicians should be aware of the risk of decline in LV systolic function in CAD patients with elevated HbA1c, and take measures as soon as possible.

Optical Fingerprint of Flat Substrate Surface and Marker-Free Lateral Displacement Detection with Angstrom-Level Precision.

We report that flat substrates such as glass coverslips with surface roughness well below 0.5 nm feature notable speckle patterns when observed with high-sensitivity interference microscopy. We uncover that these speckle patterns unambiguously originate from the subnanometer surface undulations, and develop an intuitive model to illustrate how subnanometer nonresonant dielectric features could generate pronounced interference contrast in the far field. We introduce the concept of optical fingerprint for the deterministic speckle pattern associated with a particular substrate surface area and intentionally enhance the speckle amplitudes for potential applications. We demonstrate such optical fingerprints can be leveraged for reproducible position identification and marker-free lateral displacement detection with an experimental precision of 0.22 nm. The reproducible position identification allows us to detect new nanoscopic features developed during laborious processes performed outside of the microscope. The demonstrated capability for ultrasensitive displacement detection may find applications in the semiconductor industry and superresolution optical microscopy.

Modeling of Dynamic Recrystallization Evolution for Cr8 Alloy Steel and Its Application in FEM.

In the process of Cr8 roller production, the phenomenon of coarse grain size and uneven grain size often appears, which makes the mechanical properties of the material decrease sharply. Accurate dynamic recrystallization model is the basis for predicting the change of grain size during thermal processing, and is an important basis for refining grain and improving material properties. In this study, the isothermal compression experiment was carried out on Cr8 alloy steel at 900-1200 °C and 0.005-0.1 s-1 by Gleeble -1500D thermal simulation compressor, and the stress dates of Cr8 alloy steel were obtained. According to experimental data, the Kopp dynamic recrystallization model of Cr8 alloy steel was established. The dynamic recrystallization volume fraction obtained by Kopp model was compared with that obtained by experiment at the same temperature and strain rate. The correlation value was 0.988, and the root mean square error (RMSE) was 0.053, which proved that the DRX model established was reliable. Through the secondary development of the program, the DRX model of Cr8 alloy steel was written into the software Forge® to verify the microstructure evolution model. The compression process of a cylindrical specimen of Cr8 alloy steel at 0.1 s-1 and 1050 °C was simulated, and the DRX microstructure evolution of the alloy was calculated. The comparison between the final grain size calculation results and the test metallographic photos of samples in different deformation zones shows the relative error of the grain size was less than 10.6%, indicating that the DRX model of Cr8 alloy steel can better predict the dynamic recrystallization of Cr8 alloy steel.

Manipulating the polarization dynamics in a >10-GHz Er3+/Yb3+ fiber Fabry-Pérot laser.

In this work, we report on the vector and scalar soliton dynamics that result from inevitable fiber birefringence in an 8-mm Er3+/Yb3+ fiber based Fabry-Férot (FP) laser that has a free spectral range of up to 12.5 GHz. The generation of polarization-evolving vector solitons can largely degrade the performance of application systems, and the underlying mechanisms and manipulation technologies are yet to be explored. To realize the transition from vector to scalar (linearly polarized) state, we here incorporate the polarization selection effect (PSE) in the simulation model and the numerical results verify that only a small amount of PSE is sufficient for manipulating the soliton dynamics. It also reveals that, prominent polarization-dependent intensity discrimination can be acquired via geometry-induced oblique incidence to the Bragg mirror of the semiconductor saturable absorber mirror (SESAM), and we obtain switchable operating states by tilting the SESAM in the experiments. These efforts create a feasible method to manipulate high-repetition-rate pulse and may shed light on understanding the dissipative soliton dynamics in ultrafast fiber FP lasers.