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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Dynamic gain and frequency comb formation in exceptional-point lasers

Abstract Exceptional points (EPs)—singularities in the parameter space of non-Hermitian systems where two nearby eigenmodes coalesce—feature unique properties with applications such as sensitivity enhancement and chiral emission. Existing realizations of EP lasers operate with static populations in the gain medium. By analyzing the full-wave Maxwell–Bloch equations, here we show that in a laser operating sufficiently close to an EP, the nonlinear gain will spontaneously induce a multi-spectral multi-modal instability above a pump threshold, which initiates an oscillating population inversion and generates a frequency comb. The efficiency of comb generation is enhanced by both the spectral degeneracy and the spatial coalescence of modes near an EP. Such an “EP comb” has a widely tunable repetition rate, self-starts without external modulators or a continuous-wave pump, and can be realized with an ultra-compact footprint. We develop an exact solution of the Maxwell–Bloch equations with an oscillating inversion, describing all spatiotemporal properties of the EP comb as a limit cycle. We numerically illustrate this phenomenon in a 5-μm-long gain-loss coupled AlGaAs cavity and adjust the EP comb repetition rate from 20 to 27 GHz. This work provides a rigorous spatiotemporal description of the rich laser behaviors that arise from the interplay between the non-Hermiticity, nonlinearity, and dynamics of a gain medium.

36 MATERIALS SCIENCE↗
DOE OSTI2020

OrganiCam: First Camera for Noncontact Biodetection in Space

Los Alamos National Laboratory designed a compact laser-induced fluorescence imaging camera with Raman spectrometer to identify organic molecules and biosignatures in environments such as Martian caves, icy-moons, and asteroid surfaces. OrganiCam is the primary instrument on the Laser-Induced Fluorescence Exploration of Caves for Organics and Volatiles using an Elevated Platform (LIFE COVE) NASA mission concept. OrganiCam could also determine if instruments being sent into space for NASA are sterile and analyze samples returned to Earth. OrganiCam’s robust design for extreme environments, portability, simple operation, and low power requirement build on LANL’s 50+ years designing robotic instruments for space applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Direct visualization of electromagnetic wave dynamics by laser-free ultrafast electron microscopy

Integrating femtosecond lasers with electron microscopies has enabled direct imaging of transient structures and morphologies of materials in real time and space. Here, we report the development of a laser-free ultrafast electron microscopy (UEM) offering the same capability but without requiring femtosecond lasers and intricate instrumental modifications. We create picosecond electron pulses for probing dynamic events by chopping a continuous beam with a radio frequency (RF)–driven pulser with the pulse repetition rate tunable from 100 MHz to 12 GHz. As a first application, we studied gigahertz electromagnetic wave propagation dynamics in an interdigitated comb structure. We reveal, on nanometer space and picosecond time scales, the transient oscillating electromagnetic field around the tines of the combs with time-resolved polarization, amplitude, and local field enhancement. This study demonstrates the feasibility of laser-free UEM in real-space visualization of dynamics for many research fields, especially the electrodynamics in devices associated with information processing technology.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Magnetic Field Vector Measurements Using Doppler-Free Saturation Spectroscopy

Experimentally measuring the magnetic-field vector topology in low-cost fusion-concept devices will provide critical information required to optimize and accelerate the development of those concepts for economical fusion energy. The magnetic-field measurement techniques most commonly used in modern tokamaks, i.e., beam-emission spectroscopy and optical emission spectroscopy, are not suitable below 5000 Gauss due to a lack of sensitivity. To diagnose magnetic field relevant to some of the ARPA-E-supported fusion concepts (50 to 1000 Gauss), a novel approach is required. Doppler-free saturation spectroscopy (DFSS) is a pump/probe laser-based technique and has been successfully demonstrated in the laboratory to provide a magnetic-field measurement accuracy of <10 Gauss. DFSS is implemented to obtain ultra-high-resolution spectra at a localized point in space. The spectral data is then fit to the Schrödinger equation for determination of the magnetic-field vector. To obtain the magnetic-field topology, the measurement spatial location is scanned over the desired region of space by steering the DFSS pump laser beam. The goal of this project is to assemble and commission a portable DFSS diagnostic capable of 2-D magnetic-field vector measurements utilizing the Hα spectral line profile.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Toward machine-learning-assisted PW-class high-repetition-rate experiments with solid targets

We present progress in utilizing a machine learning (ML) assisted optimization framework to study the trends in a parameter space defined by spectrally shaped, high-intensity, petawatt-class (8 J, 45 fs) laser pulses interacting with solid targets and give the first simulation-based overview of predicted trends. A neural network (NN) incorporating uncertainty quantification is trained to predict the number of hot electrons generated by the laser–target interaction as a function of pulse shaping parameters. The predictions of this NN serve as the basis function for a Bayesian optimization framework to navigate this space. For post-experimental evaluation, we compare two separate neural network (NN) models. One is based solely on data from experiments, and the other is trained only on ensemble particle-in-cell simulations. Reviewing the predicted and observed trends across the experiment-capable laser parameter search space, we find that both ML models predict a maximal increase in hot electron generation at a level of approximately 12%–18%; however, no statistically significant enhancement was observed in experiments. On direct comparison of the NN models, the average discrepancy is 8.5%, with a maximum of 30%. Since shot-to-shot fluctuations in experiments affect the observations, we evaluate the behavior of our optimization framework by performing virtual experiments that vary the number of repeated observations and the noise levels. Here, we discuss the implications of such a framework for future autonomous exploration platforms in high-repetition-rate experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Deep learning-based predictive models for laser direct drive at the Omega Laser Facility

The rich and complex physics of inertial confinement fusion provides a unique and challenging space for high-fidelity first-principles modeling. Consequently, simulation codes that are used to design experiments are computationally expensive and lack the predictive capability required for extensive parameter exploration in search of a high-performing design for laser direct drive. In this article, we present two deep-learning-based predictive models intended to address these difficulties. The first model (TL DNN) acts as a fast emulator of simulations as well as experiments at the Omega Laser Facility. This model is trained on a simulation database and subsequently calibrated on experimental data using transfer learning. To facilitate the development of this model, an autoencoder is developed to reduce the dimensionality of the input space by compressing the laser pulse input. The model predicts key experimental scalar observables of Omega experiments with high accuracy and minimal computational cost. This deep neural net enables rapid exploration of a high-dimensional input parameter space for an optimal implosion design. The second model (DNN SM+) aims to extend the statistical modeling work of Lees et al. [Phys. Rev. Lett. 127, 105001 (2021)], by increasing the complexity of the model space and allowing for coupling between degradation terms. Since the model capacity of DNN SM+ is higher than the model of Lees et al., DNN SM+ can potentially provide an improvement in predictive capability, and we use this model to provide insight into complicated degradation dependencies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Simulations of coherent electron cooling with two types of amplifiers

The SPACE code is a parallel, relativistic, three-dimensional, electromagnetic, particle-in-cell code developed for the simulations of beam dynamics and interactions. The SPACE code can perform simulations with various beam distributions, different types of boundary conditions, and flexible beam line, as well as provide sufficient processing routines for data analyses and visualization. Finally, self-consistent, highly resolved and realistic simulations were performed using the SPACE code to study the coherent electron cooling (CeC) experiment with two types of amplifiers, the free electron laser (FEL) and plasma-cascade micro-bunching amplifiers.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

High-power electrically tunable switch

A high-voltage switch, whose operation leverages the speed of electrons to generate the “on” time of the pulse in combination with the speed of light to generate the “off” time of the pulse, is described. In one example, the high-voltage switch includes a first electrode, a second electrode spaced apart from the first electrode, a region of non-absorbing material occupying a portion of the space between the first and second electrodes and allowing a laser pulse to propagate therethrough without substantial absorption, and a region of absorbing material occupying another portion of the space and producing a charged particle cloud upon receiving the laser pulse. The high-voltage switch remains “on” upon the charged particle cloud reaching an electrode and until it has been collected by the electrode, and where the high-voltage switch remains “off” subsequent to the collection and until another generated charged particle cloud reaches the electrode.

Voss, Lars↗
DOE OSTI2020

High-throughput experimentation for microstructural design in additively manufactured 316L stainless steel

In the present study, a combination of high-throughput (HT) and low-throughput (LT) techniques was used to rapidly determine the processing window and generate processing maps for Selective Laser Melting (SLM) of 316L stainless steel. The HT method includes the fabrication of hundreds of hex nut-shaped specimens, each processed with a unique combination of laser power, scanning speed, and hatch spacing. An easily removable scaffolding permitted rapid sample extraction from the base plate, thus saving machining cost and time. Hardness and immersion density measurements were used for HT characterization to identify a processing window for maximum strength and density. Within the defined processing window, a low-throughput (LT) microstructural interrogation of specimens were performed. The microstructural analysis included quantification at various length scales (i.e., grains size and morphology, texture, primary dendrite arm spacing, and melt pool geometry analysis). Microstructure-based processing maps as a function of volumetric energy density were generated. The combination of HT and LT methods produced a predictive relationship between hardness and primary dendrite arm spacing using a Hall-Petch relationship. A model is proposed to explain the dependence of microstructure on the melt pool geometry. Here, the HT method can be applied for the microstructural design of SLM-fabricated components in other alloys.

316L stainless steel↗
DOE OSTI2021

A Bayesian Approach to the Eagar–Tsai Model for Melt Pool Geometry Prediction with Implications in Additive Manufacturing of Metals

Here, this paper focuses on improving the melt pool geometry predictions and quantifying uncertainties using an adapted version of the Eagar–Tsai (E–T) model that incorporates temperature-dependent properties of the material as well as powder conditions. Additionally, Bayesian inference is employed to predict distributions for the E–T model input parameters of laser absorptivity and powder bed porosity by incorporating experimental results into the analysis. Monte Carlo uncertainty propagation is then used with these parameter distributions to estimate the melt pool depth and associated uncertainty. Our results for the 316L stainless steel suggest that both the absorptivity and powder bed porosity are strongly influenced by the laser power. In contrast, the scanning speed has only a marginal effect on both the absorptivity and powder bed porosity. We constructed a printability map using the Bayesian E–T model based on power-dependent input parameter values to demonstrate the merit of the approach. The Bayesian approach improved the accuracy in predicting the keyhole regions in the laser power-scan speed parameter space for the 316L stainless steel. Although applied to a specific adaptation of the E–T model, the method put forth can be extended to quantify uncertainties in other numerical models as well as in the estimation of unknown parameters.

316L Stainless Steel (SS).↗
DOE OSTI2025

Laboratory Demonstration of Collisionless Blob Formation via Laser-Produced Plasma Self-Focusing

Strongly localized, propagating plasma density structures that are capable of crossing magnetic field lines are known as “blobs.” Here we demonstrate a novel mechanism for the formation and propagation of an ion gyroradius-scale blob-cavity structure at the interface between a super-Alfvénic laser-produced plasma (LPP) and an ambient magnetized plasma. The LPP self-focuses along the edge of the diamagnetic cavity which results in a dense, jetlike structure as compared to ballistic motion. This collimated flow couples momentum to the ambient plasma through a collisionless process known as Larmor coupling. The Larmor electric fields locally displace the ambient ions forming a blob above the LPP flow. In the region between a gyrating blob and collimated LPP flow, a secondary cavity of expelled magnetic field forms. In conclusion, these findings are supported by particle-in-cell simulations that replicate the blob formation mechanism and provide insight to similar processes in space, astrophysical, and laboratory settings characterized by ion kinetic scales.

Fluorescence spectroscopy↗
DOE OSTI2021

SPACE CHARGE EFFECT IN LOW ENERGY MAGNETIZED ELECTRON BEAM

Magnetized electron cooling is one of the major approaches towards obtaining the required high luminosity in the proposed Electron-Ion Collider (EIC). In order to increase the cooling efficiency, a bunched electron beam with a high bunch charge and high repetition rate is required. At Jefferson Lab, we generated magnetized electron beams with high bunch charge using a new compact DC high voltage photogun biased at -300 kV with bialkali-antimonide photocathode and a commercial ultra-fast laser. This contribution discusses how magnetization affects space charge dominated beams as a function of magnetic field strength, gun high voltage, and laser pulse width, and spot size in comparison with simulations performed using General Particle Tracer.

Wijethunga, S.A.K.↗
DOE OSTI2023

Large-volume CdZnTe bar detectors characterized by laser-induced transient currents

In this work, we studied the free-carrier transport properties and space-charge formation/polarization in a CdZnTe bar-shaped radiation detector using the Laser-Induced Transient Current technique. We found out that a steady-state space charge ranging from 8 x 10 8 to 2.1 x 10 9 cm -3 is formed throughout the detector at about 0.5 s following biasing. The measured current waveforms were modeled by Monte Carlo simulations after taking into account the electric and weighting fields inside the detector and shielding box. Modeling of the unpolarized waveforms revealed an exceptionally high electron mobility-lifetime product μ e τ e ≥0.095cm 2 V -1 . The observed formation of positive space charge in the biased detector and linear scaling of the current waveform shapes on applied bias revealed that the detector polarization is attributed to carrier injection at the anode. In conclusion, measurements in pulsed and DC bias in modified electrode geometry proved the surface-charge formation.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Measurement of Kinetic-Scale Current Filamentation Dynamics and Associated Magnetic Fields in Interpenetrating Plasmas

Here, we present the first local, quantitative measurements of ion current filamentation and magnetic field amplification in interpenetrating plasmas, characterizing the dynamics of the ion Weibel instability. The interaction of a pair of laser-generated, counterpropagating, collisionless, supersonic plasma flows is probed using optical Thomson scattering (TS). Analysis of the TS ion-feature revealed anticorrelated modulations in the density of the two ion streams at the spatial scale of the ion skin depth c/ω pi = 120 μm, and a correlated modulation in the plasma current. The inferred current profile implies a magnetic field amplitude ~30 ± 6 T , corresponding to ~1% of the flow kinetic energy, indicating that magnetic trapping is the dominant saturation mechanism.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Retrieval of full angular- and energy-dependent complex transition dipoles in the molecular frame from laser-induced high-order harmonic signals with aligned molecules

High-order harmonic signals generated in molecules are the consequence of coherent summation of complex laser-induced transition dipoles $\textit{d}(θ, ω)$ with each fixed-in-space molecule; here $\theta$ is the angle of the molecular axis with respect to the laser polarization axis and $\omega$ is the harmonic energy. In the so-called rotational coherent spectroscopy, it is proposed to extract the fixed-in-space $\textit{d}(θ, ω)$ in the molecular frame by measuring harmonics generated by a probing laser from the rotational molecular wave packets that have been prepared by a prior pump laser. By varying the time delay between the two lasers, methods have been utilized to extract the $\theta$ dependence of both the amplitude and phase of each individual harmonic, but the relative phase between harmonics cannot be retrieved. Here we report that this limitation can be removed. It requires the additional measurement of harmonic spectra versus the pump-probe angles at one fixed time delay. The two-dimensional input harmonic data (time-delay and pump-probe angle) are then used to retrieve the full complex transition dipole $\textit{d}(θ, ω)$ using a retrieval method based on machine learning algorithms. Finally, we demonstrate this method on N 2 and CO 2 molecules.

74 ATOMIC AND MOLECULAR PHYSICS↗