Laser-driven Ion Acceleration Experiments Research Articles

3D track extraction from a fluorescent nuclear track detector via machine learning and an application to diagnostics of laser-driven ions.

We have developed an ion diagnostic method for laser-driven ion acceleration experiments that uses fluorescent nuclear track detectors (FNTDs). An FNTD records the particle tracks as color centers and does not require chemical etching, unlike CR-39 track detectors. The color centers are observed using a confocal laser microscope, and 3D particle tracks can be obtained by changing its focal position. The intensity of the color centers corresponds to the energy deposited by the ions. The nuclides of the ions can be determined from the intensity distribution of the color centers as a function of depth and the distance between the stopping point and the surface of the detector. To extract the intensity distribution, we must track the same ion tracks in the depth-layered microscopic images from the surface to the stopping point, even if they overlap with those of other ions. In addition, since an FNTD is sensitive not only to ions but also to electrons and photons, we must identify ion tracks among those from the latter particles. To analyze a statistical number of ion tracks, it is necessary to automate these processes. We have thus developed a method for automated ion detection and 3D tracking that relies on a support vector classifier and a kernelized correlation filter. This method was tested on a laser ion acceleration experiment performed using the J-KAREN-P laser. The method automatically detects ion tracks on FNTDs and tracks them in the depth direction. The training data are sampled from the Heavy-Ion Medical Accelerator in Chiba.

Human radiological safety assessment for petawatt laser-driven ion acceleration experiments in CLAPA-T

The newly built Compact Laser Plasma Accelerator–Therapy facility at Peking University will deliver 60 J/1 Hz laser pulses with 30 fs duration. Driven by this petawatt laser facility, proton beams with energy up to 200 MeV are expected to be generated for tumor therapy. During high-repetition operation, both prompt radiation and residual radiation may cause safety problems. Therefore, human radiological safety assessment before commissioning is essential. In this paper, we simulate both prompt and residual radiation using the Geant4 and FLUKA Monte Carlo codes with reasonable proton and as-produced electron beam parameters. We find that the prompt radiation can be shielded well by the concrete wall of the experimental hall, but the risk from residual radiation is nonnegligible and necessitates adequate radiation cooling. On the basis of the simulation results, we discuss the constraints imposed by radiation safety considerations on the annual working time, and we propose radiation cooling strategies for different shooting modes.

Automation of etch pit analyses on solid-state nuclear track detectors with machine learning for laser-driven ion acceleration.

Solid-state nuclear track detectors (SSNTDs) are often used as ion detectors in laser-driven ion acceleration experiments and are considered to be the most reliable ion diagnostics since they are sensitive only to ions and measure ions one by one. However, ion pit analyses require tremendous time and effort in chemical etching, microscope scanning, and ion pit identification by eyes. From a laser-driven ion acceleration experiment, there are typically millions of microscopic images, and it is practically impossible to analyze all of them by hand. This research aims to improve the efficiency and automation of SSNTD analyses for laser-driven ion acceleration. We use two sets of data obtained from calibration experiments with a conventional accelerator where ions with known nuclides and energies are generated and from actual laser experiments using SSNTDs. After chemical etching and scanning the SSNTDs with an optical microscope, we use machine learning to distinguish the ion etch pits from noises. From the results of the calibration experiment, we confirm highly accurate etch-pit detection with machine learning. We are also able to detect etch pits with machine learning from the laser-driven ion acceleration experiment, which is much noisier than calibration experiments. By using machine learning, we successfully identify ion etch pits ∼105 from more than 10 000 microscopic images with a precision of ≳95%. A million microscopic images can be examined with a recent entry-level computer within a day with high precision. Machine learning tremendously reduces the time consumption on ion etch pit analyses detected on SSNTDs.

Design and mathematical modeling of scintillator-based electron–ion Thomson parabola spectrometer

A compact scintillator-based electron–ion Thomson Parabola Spectrometer (ei-TPS) is designed and built up, which is able to measure the spectrum of electron and ion beams simultaneously in the same angular axis and real-time mode. The energy range of electrons is around 0.27–3.8 MeV with a relative energy resolution better than 2.5%, and the energy range of proton is around 0.16–21 MeV with a relative energy resolution better than 4% at the kinetic energy of 1 MeV, which makes it suitable for laser-driven ion acceleration experiments with 100-TW level laser. Detailed mathematical modeling is performed to reveal the dependence of properties, such as energy range and resolution, response, and detection threshold, on various parameters of ei-TPS, which is useful to modify the parameters according to specific requirements of electrons and ions.

Modeling of ion accelerated by borehole radiation pressure based on deep learning

Laser-driven ion acceleration has potential applications in high energy density matter, ion beam-driven fast ignition, beam target neutron source, warm dense matter heating, etc. Ultrashort relativistic laser interacting with solid target can generate ion beam with several hundreds of MeV in energy, and the quality of the ion beam depends strongly on the interaction parameters between the laser and the target. Development in deep learning can provide new method of analyzing the relationship between parameters in physics system, which can significantly reduce the computational and experimental cost. In this paper, a continuous mapping model of ion peak and cutoff energy is developed based on a fully connected neural network (FCNN). In the model, the dataset is composed of nearly 400 sets of particle simulations of laser-driven solid targets, and the input parameters are laser intensity, target density, target thickness, and ion mass. The model uses sparse parameter values to obtain the analysis results in a large range of parameters, which greatly reduces the computational amount of multi-dimensional parameters sweeping in a wide range. Based on the results of this model mapping, the correction formula for the ion peak energy is obtained. Furthermore, the ratio of ion cutoff energy to peak energy of each set of particle simulation is calculated. Repeating the same training process of ion peak energy and cutoff energy, the continuous mapping model of energy ratio is developed. According to the energy ratio model mapping results, the quantitative description of the relationship between ion cutoff energy and peak energy is realized, and the fitting formula for the cutoff energy of the hole-boring radiation pressure acceleration (HB-RPA) mechanism is obtained, which can provide an important reference for designing the laser-driven ion acceleration experiments.

Enhanced ion acceleration in the relativistic transparent regime due to the laser rising edge

We investigate the impacts of the laser contrast on ion acceleration when an ultra-intense laser pulse irradiates on a sub-micron foil target. In high-intensity laser driven ion acceleration experiments, the rising edge of the pulse could significantly preheat the target, which is likely to cause premature relativistic induced transparency of the target before the pulse peak. In this case, our particle-in-cell simulations show that the breakout afterburner (BOA) mechanism has obvious advantages over the radiation pressure acceleration (RPA). With the ATLAS laser contrast of 10−8.8 in 2 ps and peak intensity, the optimized target thickness is increased to 0.27 µm, where BOA works well and the maximum proton energy can reach 250 MeV. The proton energy is higher than that generated via RPA in a nanometer thin target either with and without the rising edge. Besides, the BOA appears robust against the laser contrast.

Laser-induced damage thresholds of ultrathin targets and their constraint on laser contrast in laser-driven ion acceleration experiments

Abstract Single-shot laser-induced damage threshold (LIDT) measurements of multi-type free-standing ultrathin foils were performed in a vacuum environment for 800 nm laser pulses with durations τ ranging from 50 fs to 200 ps. The results show that the laser damage threshold fluences (DTFs) of the ultrathin foils are significantly lower than those of corresponding bulk materials. Wide band gap dielectric targets such as SiN and formvar have larger DTFs than semiconductive and conductive targets by 1–3 orders of magnitude depending on the pulse duration. The damage mechanisms for different types of targets are studied. Based on the measurement, the constrain of the LIDTs on the laser contrast is discussed.

Preparation of self-supporting Au thin films on perforated substrate by releasing from water-soluble sacrificial layer

A self-supporting thin film is useful as a target material for laser-driven ion acceleration experiments. In this study, 100-nm-thick sputtered gold (Au) thin films were released from substrates using water-soluble sacrificial layers, and the released films were subsequently scooped up on perforated substrates. Au thin films were deposited by DC plasma sputtering on the sacrificial layers. In the releasing test, sodium chloride (NaCl) was shown to be most suitable as a sacrificial layer for Au thin films. In addition, sputtered Au thin films with thicknesses of 50 and 150 nm were deposited onto NaCl sacrificial layers, released on water, and scooped up on perforated substrates. Self-supporting Au thin films were obtained for all film thicknesses, but wrinkles and cracks appeared in the 50 nm film.

The precise energy spectra measurement of laser-accelerated MeV/n-class high-Z ions and protons using CR-39 detectors

The diagnosis method, using a combination of a permanent magnet and CR-39 track detectors, has been developed to separately measure the energy spectrum of the laser-accelerated MeV/n-class high-Z ions and that of MeV protons. The main role of magnet is separating between high-Z ions and protons, not for the usual energy spectrometer, while ion energy was precisely determined from careful analysis of the etch pit shapes and the etch pit growth behaviors in the CR-39. The method was applied to laser-driven ion acceleration experiments using CO2 clusters embedded in a background H2 gas. Ion energy spectra with uncertainty ΔE = 0.1 MeV n−1 for protons and carbon/oxygen ions were simultaneously obtained separately. The maximum energies of carbon/oxygen ions and protons were determined as 1.1 ± 0.1 MeV and 1.6 ± 0.1 MeV n−1, respectively. The sharp decrease around 1 MeV n−1 observed in the energy spectrum of carbon/oxygen ions could be due to a trace of the ambipolar hydrodynamic expansion of CO2 clusters. Thanks to the combination of the magnet and the CR-39, the method is robust against electromagnetic pulse (EMP).

Identification of high energy ions using backscattered particles in laser-driven ion acceleration with cluster-gas targets

Abstract A new diagnosis method for high energy ions utilizing a single CR-39 detector mounted on plastic plates is demonstrated to identify the presence of the high energy component beyond the CR-39's detection threshold limit. On irradiation of the CR-39 detector unit with a 25 MeV per nucleon He ion beam from conventional rf-accelerators, a large number of etch pits having elliptical openings are observed on the rear surface of the CR-39. Detailed investigations reveal that these etch pits are created by heavy ions inelastically backscattered from the plastic plates. This ion detection method is applied to laser-driven ion acceleration experiments using cluster-gas targets, and ion signals with energies up to 50 MeV per nucleon are identified.

The Diagnosis Method for High-Energy Ion Beams Using Backscattered Particles for Laser-Driven Ion Acceleration Experiments

The Diagnosis Method for High-Energy Ion Beams Using Backscattered Particles for Laser-Driven Ion Acceleration Experiments

The Diagnosis Method for High-Energy Ion Beams Using Backscattered Particles for Laser-Driven Ion Acceleration Experiments

A single CR-39 detector mounted on plastic plates is irradiated with a 100 MeV He ion beam. Although the beam energy is much greater than the detection threshold limit of the CR-39 detector, a large number of etch pits having elliptical openings are observed on the rear surface. Detailed investigations reveal that these etch pits are created by heavy ions inelastically backscattered from the plastic plates. This method allows a simple diagnosis of the ion beam profile and the presence of the high-energy component beyond the detection threshold limit of the CR-39 detector, especially in mixed-radiation fields such as laser-driven ion acceleration experiments.

Development of a Real-Time Ion Spectrometer with a Scintillator for Laser-Driven Ion Acceleration Experiments

A real-time ion spectrometer mainly based on a high-resolution Thomson parabola and a plastic scintillator is designed and developed. The spectrometer is calibrated by protons from an electrostatic accelerator. The feasibility and reliability of the diagnostics are demonstrated in laser-driven ion acceleration experiments performed on the XL-II laser facility. The proton spectrum extrapolated from the scintillator data is in excellent agreement with the CR39 spectrum in terms of beam temperature and the cutoff energy. This real-time spectrometer allows an online measurement of the ion spectra in single shot, which enables efficient and statistical studies and applications in high-repetition-rate laser acceleration experiments.

Development of a high resolution and high dispersion Thomson parabola

Here, we report on the development of a novel high resolution and high dispersion Thomson parabola for simultaneously resolving protons and low-Z ions of more than 100 MeV/nucleon necessary to explore novel laser ion acceleration schemes. High electric and magnetic fields enable energy resolutions of ΔE∕E < 5% at 100 MeV/nucleon and impede premature merging of different ion species at low energies on the detector plane. First results from laser driven ion acceleration experiments performed at the Trident Laser Facility demonstrate high resolution and superior species and charge state separation of this novel Thomson parabola for ion energies of more than 30 MeV/nucleon.