Optimization and control of synchrotron emission in ultraintense laser–solid interactions using machine learning – CORRIGENDUM

Effect of positive and negative defocus on contrast sensitivity in myopes and non-myopes

Laser active detection technology utilizing the cat-eye effect provides rapid response, precise positioning, and long detection distances. However, current research mainly focuses on active detection within a single visible or near-infrared band, lacking quantitative analyses of the echo spot. In this paper, a four-interval theoretical model for dual band cat-eye target echo detection was constructed using matrix optics theory and Collins diffraction integration method. Dual-band echo detection experiments were conducted using 10.6 um far-infrared waves and 532 nm visible light waves, also the power, radius, and target-missing quantities of the echo spots were collected and quantitatively compared with the theoretical results. Results indicate that, due to the diffraction limit's effect on the distribution of the echo field, the echo power of far-infrared band detection is smaller than that of visible light band detection. The impact on the light spot caused by the positive and negative defocus values is asymmetric, with positive defocus having a lower impact on the echo spot than negative defocus at the same value. A weak positive defocus value that minimizes the radius of the echo spot and maximizes the echo power exists, with the value of weak positive defocus varying between detection bands. A linear relationship exists between the incident angle of the detection laser and the deviation of the echo spot. These findings provide a foundation for extracting working band details, predicting the motion trajectory of moving cat-eye targets, and achieving real-time tracking and detection recognition during laser active detection.

It has been suggested that ‘transient surface currents’ caused by multi-MeV fast electrons can be responsible for the emission of low frequency radiation (e.g. in THz range) from ultra-intense laser–solid interactions. This mechanism has been analyzed, and analytic upper bounds on the intensity, electric field amplitude, and normalized vector potential have been developed and tested against 1D EM Particle-in-Cell simulations. The ‘transient surface current’ mechanism is effective and sufficiently efficient to fully account for all radiation that has been emitted in experiments so far.

Optical defocus influences postnatal ocular development in animal models. Induced negative lens defocus results in accelerated ocular elongation and myopia. Positive lens-induced defocus findings across animal models have been inconsistent. Specifically, in the tree shrew, positive lens-induced defocus has produced equivocal results. This study evaluated the response of the tree shrew to induced positive lens defocus. One treatment group wore positive lenses binocularly, which were increased in power sequentially from +2 to +4, +6, +8, and +9.5 D over 8 weeks. Other groups wore +4, +6, and +9.5 D lenses, respectively, for 8 weeks. Animals wearing zero-powered (plano) lenses served as controls. Refractive error and ocular dimensions were measured at the start of treatment and every week thereafter. Sequentially increasing positive lens power caused a relative hyperopia of +5.6 D (p < 0.01) compared to the plano lens group (+10.9 +/- 1.8 D vs +5.3 +/- 0.5 D). Constant +4 D lens wear produced +6.9 D relative hyperopia, while +6 and +9.5 D lens wear did not induce hyperopia. Lens-induced defocus changes in refractive state were significantly correlated with vitreous chamber depth changes. The threshold for consistent responses to positive lens defocus in tree shrew was between +4 and +6 D. The results will enable targeted investigation of the efficacy of positive lens defocus in inhibiting myopic ocular growth.

A positron production experiment was performed by irradiating an ultra-intense picosecond laser on solid tantalum targets. Quasi-monoenergetic positron beams were obtained owing to the sheath field on the back of the target. The experiment shows that the peak energy of the positron spectrum has a linear relation with the reciprocal of the target diameter. A simple analytical model of the sheath field was constructed to explain the experimental data, which predicts the positron peak energy in terms of the target diameter and hot electron parameters. Based on the field model, Monte Carlo simulations were conducted to treat the positron production and acceleration self-consistently. The simulated spectra are in good agreement with most experiment results. The disagreement of the 1 mm diameter data reveals that the hot electron propagation along the target flank surface plays an important role in the sheath field set up. Several aspects involved in the positron acceleration are discussed.

Short-term axial eye length changes in response to imposed positive and negative defocus were compared in hyperopic, emmetropic and myopic young adults to learn about possible differences in emmetropization. Thirty-seven subjects (average age: 28±4 years) participated: emmetropes (n=15), myopes (n=15), and hyperopes (n=7). They viewed a 30-minute movie on a large TV screen (65″) at 2-meter distance (equivalent to -0.5D) with optical corrections, while a+3.5 D (myopic defocus) or -3.5 D (hyperopic defocus) lens was added in the right eye. A subset of myopes (n=14) was also tested with -2 D lenses. Axial length was measured in both eyes before and after viewing using the Haag-Streit Lenstar LS 900. With+3.5 D myopic defocus, emmetropes (-9.7±13.1µm) and hyperopes (-8.9±5.6µm) exhibited significant axial shortening, while myopes (-1.1±10.2µm) did not. Hyperopes and myopes differed significantly, but emmetropes and hyperopes did not. With -3.5 D hyperopic defocus, both emmetropic (+5.0±7.5µm) and hyperopic eyes (+6.6±6.9µm) elongated, indicating that their retina distinguished positive from negative defocus. Myopic eyes displayed paradoxical axial eye shortening (-7.1±8.6µm). Hyperopes and myopes differed significantly, but emmetropes and hyperopes did not. Reducing the lens power to -2 D abolished the shortening in myopes. Group data indicate bidirectional, sign-of-defocus-dependent axial length changes occur in both emmetropic and hyperopic eyes, indicating similar retinal function. Myopes showed reduced or even reversed responses, showing a functional deficiency in the myopic retina.

Role of power on physiochemical properties of Mo- and Ni-based nanoparticles manufactured by laser ablation

Irradiating a metal wire with an intense femtosecond laser pulse induces a terahertz (THz) surface wave that travels along the wire. Here, the characteristics of the THz surface wave generated by the laser–wire interaction are investigated in detail by using an electro-optical method to determine the dependence of surface wave properties on laser energy and wire diameter. The surface wave is distributed by the Hankel function in the wire radial direction. On the wire surface, the electric field is estimated to be MV/cm. The peak electric field of the surface wave and the conversion efficiency from laser energy to surface wave energy are found to be proportional to the laser energy raised to the power of 0.67 and 0.3, respectively.

The durability and long-term survival of medical implants are major concerns for patients and surgeons. The laser shock peening (LSP) process can enhance the implant’s in-vivo lifespan through the compressive residual stress introduced on the implant’s surface. In the current research, a novel hybrid machine learning (ML) prediction tool was developed to calculate LSP induced residual stresses. Laser energies of 3 J, 5 J, 7 J with three overlapping levels of 33%, 50% and 67% with a constant laser spot diameter were introduced to a Ti-6Al-7Nb titanium hip implant material. A three-dimensional finite element model was developed incorporating an explicit dynamic analysis to capture the dynamic material response during the LSP process. Furthermore, The random forest ML algorithm was adapted so that the laser energy and overlapping were set as input parameters, while the associated residual stresses were set as output parameters. The mean squared error (MSE), root MSE and coefficient of determination for testing data sets concerning residual stress were 112.9%, 10.6% and 97%, respectively. The FEM and ML results both show a good agreement with the experimental data. The new proposed approach allows development of ML models even with a limited experimental data. The accuracy and performance of each model are discussed and the limitations are addressed. The approach carried out in this paper enables subsequent predictions of surface treatment techniques of implants through residual stress fields and can be applied to a wide range of applications.

266nm UV laser has a wide range of applications in many fields, such as laser medical treatment, laser processing, precision measure and other applications for the reason of its advantages in wavelength, small diffraction effects, high single-photon energy, and high resolution and so on. BBO crystals absorb parts of the fundamental laser energy and second harmonic laser energy are unavoidable, and thus the temperature raise, so that the existing crystal phase matching conditions change, resulting in phase mismatching in the high-power frequency doubling, greatly influence the 266nm UV laser conversion efficiency. To further study the effect of phase mismatching to conversion efficiency, and improve the conversion efficiency, output power and other output characteristics of 266nm laser, the article mainly describe from the following three aspects. Firstly, took the use of three-dimensional nonlinear crystal temperature distribution which is obtained, the process of BBO crystal thermal-induced phase mismatching is analyzed. Secondly, based on frequency doubling theory, the effects of the thermal-induced phase mismatching affected of conversion in crystals are analyzed. Combining with the phase mismatching of the three-dimensional distributions, the fourth harmonic conversion efficiency with thermal phase mismatching changes of BBO 266nm UV laser are simulated for the first time. Thirdly, by using MATLAB software, the effects of phase mismatching to conversion efficiency in crystal for different waist radius, 532nm laser power and the fundamental beam quality are simulated. The results indicate a good physical interpretation of reasons of high power laser frequency doubling system. It shows that the model established explains the reason of the reduction of conversion efficiency, output power and the beam quality excellently. All results make a leading sense to the research on the compensating of the phase mismatching and on the improvement of conversion efficiency.

&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;The Exhaust Emission Control is a vital part of automotive development aimed at ensuring effective control of pollutants such as NOx, CO, and HC. The traditional method of calibrating emission control strategies is a highly time-consuming process, which requires extensive vehicle testing under a variety of operating conditions. The frequent updates in emission legislation requires a high-efficiency process to achieve a faster time-to-market. The use of Machine Learning (ML) in the domain of emission calibration is the need of the hour to proactively improve the process efficiency and achieve a faster time-to-market. This paper attempts to explores emerging trend of Machine Learning (ML) based data analysis that have improved the overall process efficiency of emission control calibration. The data generated by automated programs could be used directly in data analysis with minimal or no need for data cleaning. The Machine Learning (ML) models could be trained by historical data from relevant engine platforms to predict the output. The integration of Machine Learning (ML) models with automated measurement processes further enhances the process by enabling model-based calibration development. The use of automated programs and machine learning (ML) models could ensure high accuracy of the emission calibration data. This methodology could significantly reduce the need for volumes of measurements required for data analysis and calibration. This could further help in optimized usage of testing facilities, ultimately saving time and resources. A 70% overall savings in time and resources could be expected with the use of automation and machine learning models. This methodology also supports faster calibration development cycles that would be required for adhering to frequent legislative changes and achieving faster time-to-market.&lt;/div&gt;&lt;/div&gt;

A flexible, on-line magnetic spectrometer for ultra-intense laser produced fast electron measurement

The development of flexible thermoelectric (TE) generators is essential for powering next‐generation wearable and Internet‐of‐Things (IoT) devices. Yet, conventional fabrication routes for benchmark Bi 2 Te 3 ‐based materials are restricted to rigid and small‐area devices. Emerging printing methods like laser powder bed fusion (LPBF) offer scalability, flexibility, and freeform shaping, but at the expense of jeopardizing performance. In this study, machine learning (ML) is applied to optimize the processing of LPBF‐fabricated Bi 0.5 Sb 1.5​ Te 3 ‐based materials printed on a flexible substrate. The developed ML tool identifies Sb concentration, printing atmosphere, and, to a lesser extent, laser energy, as the key processing parameters governing performance. The algorithm also prescribes the exact parameter values that maximize performance. The ML model not only supports the trend observed from the exhaustive traditional search of the experimental space, but it also enables a slight further improvement in average power factor, reaching a consistent ∼1280 µW m −1 K −2 value. A flexible 4 cm 2 ‐large, printed TE energy harvesting module produced with the optimized materials displays a power output of 44 µW at Δ T = 30 K. This work advances data‐driven TE materials manufacturing and enhances the understanding of LPBF processing‐property relationships, paving the way for next‐generation high‐performance, flexible TE generators.

In the scheme of fast ignition of inertial confinement fusion, the fuel temperature mainly relies on fast electrons, which act as an energy carrier, transferring the laser energy to the fuel. Both conversion efficiency from the laser to the fast electron and the energy spectrum of the fast electron are essentially important to achieve highly effective heating. In this study, a two-dimensional particle in cell simulation is applied to study the generation of fast electrons from solid-density plasmas with different laser waveforms. The results have shown that the slope of the rising edge has a significant effect on fast electron generation and energy absorption. For the negative skew pulse with a relatively slow rising edge, the J×B mechanism can most effectively accelerate the electrons. The overall absorption efficiency of the laser energy is optimized, and the fast electron yield in the middle- and low-energy range is also improved.

The purpose of this research is the study of the laser welding process of the aluminum alloy 5182 and the development of models by means of the COSMOS/M package, in order to predict the shape of the keyhole and the temperatures profile of the weld. Modeling has been done considering the degree of defocusing. The heat flow applied on the models was a Gauss flow, considering the condition of the focused face and the conditions of negative and positive defocusing. The validity of the models has been demonstrated comparing their results with those obtained by experimental tests. The extent of defocusing of laser beam affected the stability of the keyhole and welding geometry.