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At least 1,531 records · Page 85
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NASA NTRS2006

Investigations of Stratosphere-Troposphere Exchange of Ozone Derived From MLS Observations

Daily high-resolution maps of stratospheric ozone have been constructed using observations by MLS combined with trajectory information. These fields are used to determine the extratropical stratosphere-troposphere exchange (STE) of ozone for the year 2005 using two diagnostic methods. The resulting two annual estimates compare well with past model- and observational-based estimates. Initial analyses of the seasonal characteristics indicate that significant STE of ozone in the polar regions occurs only during spring and early summer. We also examine evidence that the Antarctic ozone hole is responsible for a rapid decrease in the rate of ozone STE during the SH spring. Subtracting the high-resolution stratospheric ozone fiom OMI total column measurements creates a high-resolution tropospheric ozone residual (HTOR) product. The HTOR fields are compared to the spatial distribution of the ozone STE. We show that the mean tropospheric ozone maxima tend to occur near locations of significant ozone STE. This suggests that STE may be responsible for a significant fraction of many mean tropospheric ozone anomalies.

Olsen, Mark A.↗
NASA NTRS2012

Qualification of a Null Lens Using Image-Based Phase Retrieval

In measuring the figure error of an aspheric optic using a null lens, the wavefront contribution from the null lens must be independently and accurately characterized in order to isolate the optical performance of the aspheric optic alone. Various techniques can be used to characterize such a null lens, including interferometry, profilometry and image-based methods. Only image-based methods, such as phase retrieval, can measure the null-lens wavefront in situ - in single-pass, and at the same conjugates and in the same alignment state in which the null lens will ultimately be used - with no additional optical components. Due to the intended purpose of a Dull lens (e.g., to null a large aspheric wavefront with a near-equal-but-opposite spherical wavefront), characterizing a null-lens wavefront presents several challenges to image-based phase retrieval: Large wavefront slopes and high-dynamic-range data decrease the capture range of phase-retrieval algorithms, increase the requirements on the fidelity of the forward model of the optical system, and make it difficult to extract diagnostic information (e.g., the system F/#) from the image data. In this paper, we present a study of these effects on phase-retrieval algorithms in the context of a null lens used in component development for the Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission. Approaches for mitigation are also discussed.

Bolcar, Matthew R.↗
NASA NTRSDate not supplied

Use of three-cornered hat error estimates in MERRA-2 to guide an improved reanalysis-Part 1

The three-cornered hat (3CH) method estimates the uncertainties of three different co-located model or observational data sets (Anthes and Rieckh, 2018; Sjoberg et al., 2021). Rieckh et al. (2021) used the 3CH method to compare the random error statistics of different global forecast and reanalysis models, as well as radio occultation (RO) and radiosonde observations. That study showed that the MERRA-2 reanalysis, while having smaller errors in the stratosphere than its predecessor MERRA, had larger errors in the troposphere than many of the other data sets analyzed. The MERRA-2 errors were particularly large in the tropics. In a collaborative effort between UCAR’s COSMIC (Constellation Observing System for Meteorology, Ionosphere and Meteorology) program and NASA’s Global Modeling and Assimilation Office (GMAO), we carried out further 3CH error diagnostics to help isolate the causes of these larger errors and help guide the development of an improved reanalysis. This presentation summarizes random error statistics associated with MERRA-2, ECMWF’s ERA5 reanalysis, and COSMIC-2 (C2) RO observations. We compute 3CH error variance estimates of refractivity, as well as temperature and specific humidity using UCAR’s COSMIC Data Analysis and Archive Center (CDAAC) improved 1D-variational (1D-Var) retrieval (wetPf2) over 15 latitude bands from 45S to 45N. The 1D-Var retrievals of specific humidity and temperature for C2 use NCEP’s Global Forecast System (GFS) as the background. Anthes et al. (2021) showed that it gives accurate estimates of temperature and specific humidity in the tropics and subtropics, even in the challenging environment of intense Hurricane Dorian (2019). This presentation confirms the previous results that MERRA-2 has significantly larger errors in the tropics and subtropics than either C2 or ERA5. Its errors are larger between 30S and 30N compared to 30-45 N-S latitudes, and are also larger over land compared to oceans. Most of the MERRA-2 refractivity errors come from specific humidity, except over land below 3 km where temperature errors are large. These results suggest that moist convection and atmospheric boundary layer physics in MERRA-2 may be responsible for a significant part of the higher uncertainties. These results are being used to guide GMAO in developing an improved next-generation reanalysis, as shown in a companion presentation submitted to this conference (El Akkraoui et al., 2021), which extends this study and describes improvements to MERRA-2 leading to the next GMAO reanalysis.

Jeremiah Sjoberg↗
NASA NTRS2022

Satellite Precipitation Measurements: What Have We Learnt About Cloud-Precipitation Processes From Space?

Precipitation is one of the fundamental elements that define global and regional climatology. Precipitation systems consist of a broad spectrum of three-dimensional structures in which microphysical processes interact with macro-scale processes in the cloud system and the ambient environment that prescribe the evolution of the system. Since 1970s, satellite observations of precipitation have been a fundamental tool in quantifying this complex interaction. They have first quantified the frequency and intensity of global precipitation, including remote areas over open oceans and polar regions, thus providing today’s precipitation climatology. More recently, satellite observations of cloud and precipitation have been exploited for understanding the physical mechanisms governing precipitation systems. A subset of these studies also provided observation-based metrics to probe physical processes operating in cloud-precipitation systems and to apply them as diagnostic measures for evaluating the representation of the processes in numerical models for better projections of future climate. In this chapter, we first review the theoretical basis of precipitation remote sensing from space and describe how it is practically applied in satellite missions. In the first part of the chapter, an historical overview of the satellite missions is described, summarising the instruments and retrieval algorithms developed in the missions. In the second part, we introduce a set of studies discussing the fundamental mechanisms behind precipitation formation, highlighting what we have learnt to date on cloud-precipitation processes from satellite observations.

Precipitation↗
NASA NTRSDate not supplied

Auroral ovals versus flare ribbons: Optical footprints of explosive magnetic field reconfiguration in Earth’s magnetosphere and the Sun’s corona

Despite drastically different plasma conditions in the two systems, eruptive energy release events in solar active regions and in Earth’s magnetosphere have a lot in common. Both solar active region eruptions and the substorm activity in the nightside magnetosphere are known to be associated with an abrupt large-scale reorganization of the supporting magnetic systems enabling the conversion and dissipation of the stored free magnetic energy. The rate of energy accumulation in either system tends to be by orders of magnitude slower than the energy release rate, leading to the formation of an impulsive loading-unloading cycle involving a relatively long pre-reconnection phase (substorm growth phase, pre-flare stressing of an active region magnetic field), a short and explosive reconnection phase (substorm breakup and expansion, eruptive flares and CMEs), and a prolonged post-reconnection phase (substorm recovery phase and the post-flare active region reconfiguration). In Earth’s magnetosphere, this loading-unloading cycle is diagnosed by monitoring characteristic changes in the particle precipitation pattern in the northern and southern auroral ovals marking the boundary between the open and close magnetic flux. The position, shape, structure, and dynamics of the auroral borealis were shown to communicate critically important information about an upcoming substorm, the location and timing of the initial reconnection onset, and the subsequent return of the magnetosphere to a lower-energy state. On the Sun, a similar role is played by the chromospheric flare ribbons which enable a detailed diagnostics of the overlying reconnecting magnetic field. In this talk, we’ll discuss similarities and differences in using auroral and flare ribbon observations for monitoring eruptive energy release in respectively Earth’s magnetosphere and solar corona. Special emphasis will be placed on the quantitative interpretation of the two types of optical signatures for empirical diagnostics of the underlying reconnection activity and for constraining its theoretical models. We’ll also compare forecasting capabilities of the two types of optical signatures in the context of space weather prediction objectives.

V. M. Uritskiy↗
DOE OSTI2016

Automatic anatomy recognition in whole-body PET/CT images

Purpose: Whole-body positron emission tomography/computed tomography (PET/CT) has become a standard method of imaging patients with various disease conditions, especially cancer. Body-wide accurate quantification of disease burden in PET/CT images is important for characterizing lesions, staging disease, prognosticating patient outcome, planning treatment, and evaluating disease response to therapeutic interventions. However, body-wide anatomy recognition in PET/CT is a critical first step for accurately and automatically quantifying disease body-wide, body-region-wise, and organwise. This latter process, however, has remained a challenge due to the lower quality of the anatomic information portrayed in the CT component of this imaging modality and the paucity of anatomic details in the PET component. In this paper, the authors demonstrate the adaptation of a recently developed automatic anatomy recognition (AAR) methodology [Udupa et al., “Body-wide hierarchical fuzzy modeling, recognition, and delineation of anatomy in medical images,” Med. Image Anal. 18, 752–771 (2014)] to PET/CT images. Their goal was to test what level of object localization accuracy can be achieved on PET/CT compared to that achieved on diagnostic CT images. Methods: The authors advance the AAR approach in this work in three fronts: (i) from body-region-wise treatment in the work of Udupa et al. to whole body; (ii) from the use of image intensity in optimal object recognition in the work of Udupa et al. to intensity plus object-specific texture properties, and (iii) from the intramodality model-building-recognition strategy to the intermodality approach. The whole-body approach allows consideration of relationships among objects in different body regions, which was previously not possible. Consideration of object texture allows generalizing the previous optimal threshold-based fuzzy model recognition method from intensity images to any derived fuzzy membership image, and in the process, to bring performance to the level achieved on diagnostic CT and MR images in body-region-wise approaches. The intermodality approach fosters the use of already existing fuzzy models, previously created from diagnostic CT images, on PET/CT and other derived images, thus truly separating the modality-independent object assembly anatomy from modality-specific tissue property portrayal in the image. Results: Key ways of combining the above three basic ideas lead them to 15 different strategies for recognizing objects in PET/CT images. Utilizing 50 diagnostic CT image data sets from the thoracic and abdominal body regions and 16 whole-body PET/CT image data sets, the authors compare the recognition performance among these 15 strategies on 18 objects from the thorax, abdomen, and pelvis in object localization error and size estimation error. Particularly on texture membership images, object localization is within three voxels on whole-body low-dose CT images and 2 voxels on body-region-wise low-dose images of known true locations. Surprisingly, even on direct body-region-wise PET images, localization error within 3 voxels seems possible. Conclusions: The previous body-region-wise approach can be extended to whole-body torso with similar object localization performance. Combined use of image texture and intensity property yields the best object localization accuracy. In both body-region-wise and whole-body approaches, recognition performance on low-dose CT images reaches levels previously achieved on diagnostic CT images. The best object recognition strategy varies among objects; the proposed framework however allows employing a strategy that is optimal for each object.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

WHAT ARE THE Omh {sup 2} ( z {sub 1}, z {sub 2}) AND Om ( z {sub 1}, z {sub 2}) DIAGNOSTICS TELLING US IN LIGHT OF H ( z ) DATA?

The two-point diagnostics Om ( z {sub i} , z {sub j} ) and Omh {sup 2}( z {sub i} , z {sub j} ) have been introduced as an interesting tool for testing the validity of the Λ cold dark matter (ΛCDM) model. Recently, Sahni et al. combined two independent measurements of H ( z ) from baryon acoustic oscillation (BAO) data with the value of the Hubble constant H {sub 0}, and used the second of these diagnostics to test the ΛCDM (a constant equation-of-state parameter for dark energy) model. Their result indicated a considerable tension between observations and predictions of the ΛCDM model. Since reliable data concerning the expansion rates of the universe at different redshifts H ( z ) are crucial for the successful application of this method, we investigate both two-point diagnostics on the most comprehensive set of N = 36 measurements of H ( z ) from BAOs and the differential ages (DAs) of passively evolving galaxies. We discuss the uncertainties of the two-point diagnostics and find that they are strongly non-Gaussian and follow the patterns deeply rooted in their very construction. Therefore we propose that non-parametric median statistics is the most appropriate way of treating this problem. Our results support the claims that ΛCDM is in tension with H ( z ) data according to the two-point diagnostics developed by Shafieloo, Sahni, and Starobinsky. However, other alternatives to the ΛCDM model, such as the wCDM or Chevalier–Polarski–Linder models, perform even worse. We also note that there are serious systematic differences between the BAO and DA methods that ought to be better understood before H ( z ) measurements can compete with other probes methods.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Huge ensembles – Part 2: Properties of a huge ensemble of hindcasts generated with spherical Fourier neural operators

Abstract. In Part 1, we created an ensemble based on spherical Fourier neural operators. As initial condition perturbations, we used bred vectors, and as model perturbations, we used multiple checkpoints trained independently from scratch. Based on diagnostics that assess the ensemble's physical fidelity, our ensemble has comparable performance to operational weather forecasting systems. However, it requires orders-of-magnitude fewer computational resources. Here in Part 2, we generate a huge ensemble (HENS), with 7424 members initialized each day of summer 2023. We enumerate the technical requirements for running huge ensembles at this scale. HENS precisely samples the tails of the forecast distribution and presents a detailed sampling of internal variability. HENS has two primary applications: (1) as a large dataset with which to study the statistics and drivers of extreme weather and (2) as a weather forecasting system. For extreme climate statistics, HENS samples events 4σ away from the ensemble mean. At each grid cell, HENS increases the skill of the most accurate ensemble member and enhances coverage of possible future trajectories. As a weather forecasting model, HENS issues extreme weather forecasts with better uncertainty quantification. It also reduces the probability of outlier events, in which the verification value lies outside the ensemble forecast distribution.

Mahesh, Ankur↗
NASA NTRS1990

Gear noise, vibration, and diagnostic studies at NASA Lewis Research Center

The NASA Lewis Research Center and the U.S. Army Aviation Systems Command are involved in a joint research program to advance the technology of rotorcraft transmissions. This program consists of analytical as well as experimental efforts to achieve the overall goals of reducing weight, noise, and vibration, while increasing life and reliability. Recent analytical activities are highlighted in the areas of gear noise, vibration, and diagnostics performed in-house and through NASA and U.S. Army sponsored grants and contracts. These activities include studies of gear tooth profiles to reduce transmission error and vibration as well as gear housing and rotordynamic modeling to reduce structural vibration transmission and noise radiation, and basic research into current gear failure diagnostic methodologies. Results of these activities are presented along with an overview of near term research plans in the gear noise, vibration, and diagnostics area.

Zakrajsek, James J.↗
DOE OSTI2022

Uncertainties in Atomic Data for Modeling Astrophysical Charge Exchange Plasmas

Relevant uncertainties of theoretical atomic data are vital to determining the accuracy of plasma diagnostics in a number of areas, including, in particular, the astrophysical study. We present a new calculation of the uncertainties on the present theoretical ion-impact charge exchange atomic data and X-ray spectra, based on a set of comparisons with the existing laboratory data obtained in historical merged-beam, cold-target recoil-ion momentum spectroscopy, and electron beam ion traps experiments. The average systematic uncertainties are found to be 35–88% on the total cross sections, and 57–75% on the characteristic line ratios. The model deviation increases as the collision energy decreases. The errors on total cross sections further induce a significant uncertainty to the calculation of ionization balance for low-temperature collisional plasmas. Substantial improvements of the atomic database and dedicated laboratory measurements are needed to obtain the current models, ready for the X-ray spectra from the next X-ray spectroscopic mission.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Spatiotemporal measurements of striations in a glow discharge’s positive column using laser-collisional induced fluorescence

Here we have observed the behavior of striations caused by ionization waves propagating in low-pressure helium DC discharges using the non-invasive laser-collision induced fluorescence (LCIF) diagnostic. To achieve this, we developed an analytic fit of collisional radiative model (CRM) predictions to interpret the LCIF data and recover quantitative two-dimensional spatial maps of the electron density, n e , and the ratios of LCIF emission states that can be correlated with T e with the use of accurate distribution functions at localized positions within striated helium discharges at 500 mTorr, 750 mTorr, and 1 Torr. To our knowledge, these are the first spatiotemporal, laser-based, experimental measurements of n e in DC striations. The n e and 447:588 ratio distributions align closely with striation theory. Constriction of the positive column appears to occur with decreased gas pressure, as shown by the radial n e distribution. We identify a transition from a slow ionization wave to a fast ionization wave between 750 mTorr and 1 Torr. These experiments validate our analytic fit of n e , allowing the implementation of an LCIF diagnostic in helium without the need to develop a CRM.

42 ENGINEERING↗
DOE OSTI2016

Predictions for Gyro-phase Drift in MDPX

This work assesses the feasibility of observing the gyro-phase drift in the Auburn Magnetized Dusty Plasma Experiment [MDPX, described by Thomas et al., Plasma Phys. Controlled Fusion 54, 124034 (2012)]. The gyro-phase drift arises when a dust grain does not instantaneously reach the in-situ-equilibrium grain charge during gyro-synchronous grain-charge modulation. Koepke et al. [J. Plasma Phys. 79, 1099 (2013)] first suggested using MDPX to observe the gyro-phase drift, and here we use a single-particle trajectory tracker with an iterative velocity solver, using a fixed timestep for grain motion and an adaptive time step for grain charging, to consider all relevant dust grain forces to assess gyro-phase drift arising from gradual inhomogeneity. Additionally, the semi-analytic theory developed by Walker et al. [J. Plasma Phys. 80, 395 (2014)] predicts dust grain motion in abrupt inhomogeneity for MDPX-relevant conditions. We compare three grain-charging models with each other and with the single-particle trajectory tracker and found to predict distinctly different trajectories depending on the treatment of neutral drag and flowing ions. The measurement thresholds for Particle Tracking Velocimetry permit gyro-phase drift detection in MDPX for the abrupt inhomogeneity, given sufficiently large enough UV photoelectron flux (fuv/[n e v the ] > 0.01) and low enough neutral gas pressure (less than one mTorr). The Orbit-Motion-Limited charge model and the charge models developed by Patacchini et al. [Phys. Plasmas 14, 062111 (2007)] and Gatti and Kortshagen [Phys. Rev. E 78, 046402 (2008)] can, in principle, be distinguished by gyro-phase drift in the abrupt inhomogeneity, but large magnetic fields, large UV photoelectron flux, and low neutral gas pressure are required. Gyro-phase drift for a gradual inhomogeneity in the ratio ne/ni, arising from the presence of a radial electric field, is predicted to be undetectable.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2012

CHARGE STATE EVOLUTION IN THE SOLAR WIND. II. PLASMA CHARGE STATE COMPOSITION IN THE INNER CORONA AND ACCELERATING FAST SOLAR WIND

In the present work, we calculate the evolution of the charge state distribution within the fast solar wind. We use the temperature, density, and velocity profiles predicted by Cranmer et al. to calculate the ionization history of the most important heavy elements in the solar corona and solar wind: C, N, O, Ne, Mg, Si, S, and Fe. The evolution of each charge state is calculated from the source region in the lower chromosphere to the final freeze-in point. We show that the solar wind velocity causes the plasma to experience significant departures from equilibrium at very low heights, well inside the field of view (within 0.6 R{sub sun} from the solar limb) of nearly all the available remote-sensing instrumentation, significantly affecting observed spectral line intensities. We also study the evolution of charge state ratios with distance from the source region, and the temperature they indicate if ionization equilibrium is assumed. We find that virtually every charge state from every element freezes in at a different height, so that the definition of freeze-in height is ambiguous. We also find that calculated freeze-in temperatures indicated by charge state ratios from in situ measurements have little relation to the local coronal temperature of the wind source region, and stop evolving much earlier than their correspondent charge state ratio. We discuss the implication of our results on plasma diagnostics of coronal holes from spectroscopic measurements as well as on theoretical solar wind models relying on coronal temperatures.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

An Upper Limit on the Milky Way Mass from the Orbit of the Sagittarius Dwarf Satellite

As one of the most massive Milky Way (MW) satellites, the Sagittarius dwarf galaxy played an important role in shaping the Galactic disk and stellar halo morphologies. The disruption of Sagittarius over several close-in passages has populated the halo of our Galaxy with large-scale tidal streams and offers a unique diagnostic tool for measuring its gravitational potential. Here, we test different progenitor mass models for the MW and Sagittarius by modeling the full infall of the satellite. We constrain the mass of the Galaxy based on the kinematics of the satellite remnant and multiple tidal streams of Sagittarius. Our semianalytic modeling of the orbital dynamics agrees with full N-body simulations, and favors low values for the MW mass, ≲10{sup 12} M{sub ⊙}. This conclusion eases the tension between ΛCDM and the observed parameters of the MW satellites.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Low latency optical-based mode tracking with machine learning deployed on FPGAs on a tokamak

Active feedback control in magnetic confinement fusion devices is desirable to mitigate plasma instabilities and enable robust operation. Optical high-speed cameras provide a powerful, non-invasive diagnostic and can be suitable for these applications. Here, in this study, we process high-speed camera data, at rates exceeding 100 kfps, on in situ field-programmable gate array (FPGA) hardware to track magnetohydrodynamic (MHD) mode evolution and generate control signals in real time. Our system utilizes a convolutional neural network (CNN) model, which predicts the n = 1 MHD mode amplitude and phase using camera images with better accuracy than other tested non-deep-learning-based methods. By implementing this model directly within the standard FPGA readout hardware of the high-speed camera diagnostic, our mode tracking system achieves a total trigger-to-output latency of 17.6 μs and a throughput of up to 120 kfps. This study at the High Beta Tokamak-Extended Pulse (HBT-EP) experiment demonstrates an FPGA-based high-speed camera data acquisition and processing system, enabling application in real-time machine-learning-based tokamak diagnostic and control as well as potential applications in other scientific domains.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1980

Theoretical profiles for the 1-0 S/1/ H2 line in carbon stars

The spectra of carbon stars have been synthesized from the models of Querci, Querci, and Tsuji and Querci and Querci in the region of the 1-0 S(1) vibration-rotation quadrupole line of H2. The line is shown to be sufficiently strong to be seen against the numerous lines of the CN red system for models with effective temperatures less than about 2700 K. The usefulness of the line as a diagnostic of the atmosphere is discussed, and a comparison with the measured spectra of UU Aur and S Cep is made. It is concluded that the outer atmospheric layers of carbon stars are significantly warmer than the models predict. An additional opacity source in the outer layers is required.

Goorvitch, D.↗
DOE OSTI2021

First-principles modeling of plasmons in aluminum under ambient and extreme conditions

The theoretical understanding of plasmon behavior is crucial for an accurate interpretation of inelastic scattering diagnostics in many experiments. In this work, we highlight the utility of linear response time-dependent density functional theory (LR-TDDFT) as a first-principles framework for consistently modeling plasmon properties. We provide a comprehensive analysis of plasmons in aluminum from ambient to warm dense matter conditions and assess typical properties such as the dynamical structure factor, the plasmon dispersion, and the plasmon lifetime. We compare our results with scattering measurements and with other TDDFT results as well as models such as the random phase approximation, the Mermin approach, and the dielectric function obtained using static local field corrections of the uniform electron gas parametrized from path-integral Monte Carlo simulations. We conclude that results for the plasmon dispersion and lifetime are inconsistent between experiment and theories and that the common practice of extracting and studying plasmon dispersion relations is an insufficient procedure to capture the complicated physics contained in the dynamic structure factor in its full breadth.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Capabilities of laser technology for manufacturing diagnostic peptide matrices with maximal density

The process of manufacturing a matrix-gel biochip is modelled by means of laser fused deposition of a layer of polymer microparticles, containing a sensitive peptide element, onto a glass substrate. The limits of acceptable ranges and the optimal values of laser parameters, at which the melting of the polymer coating occurs without damaging the sensitive elements of the biochip, are theoretically determined. The results of the experiments on laser fused deposition of a layer of microparticles having the size 3 – 4 μm confirm the conservation of the functions of the biological complexes at optimal irradiation regimes. The parameters of the laser impact affecting the possible minimal separation between the zones of laser fused deposition are investigated. The essential role of heat conductivity and thermoplasticity of the polymer in increasing the size of the melted droplet is demonstrated. Using the laser radiation with the wavelength 532 nm focused into a spot with the diameter 6 μm (the laser pulse duration being 10 ms) the laser fused deposition density of 110000 spots per 1 cm{sup 2} is achieved. The maximal estimated density of laser fused deposition for the studied system amounts to 250000 spots per 1 cm{sup 2}. (biophotonics)

36 MATERIALS SCIENCE↗