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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 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Theory of In-Cloud Activation of Aerosols and Microphysical Quasi-Equilibrium in a Deep Updraft

The microphysical quasi-equilibrium in an ascending adiabatic parcel is elucidated by an analytical theory in 0D with drastic simplifications. The theory predicts how in-cloud activation is most likely to be triggered by the onset of precipitation during sufficient ascent, with the ascent only needing to approach almost twice the cloud-base updraft speed aloft. The precipitation and cloud condensate mass fields are coupled in a closed system in a simplified version of the model. The initial state of no precipitation is unstable with respect to a perturbation. In the 2D phase space of both mass fields, there is a neutral line. Unstable growth of precipitation mass drives the system to cross the line into a regime of stability. An attractor is then approached consisting of precipitation mass balanced by accretion of cloud mass and fallout. The cloud-particle number concentration also approaches a stable equilibrium governed by the balance between in-cloud activation aloft from the inexorably increasing supersaturation during vertical acceleration and accretion of cloud droplets by precipitation. Dimensionless numbers characterizing the microphysical equilibria and their stability are derived mathematically, including a condensation–precipitation efficiency and an in-cloud activation efficiency. The theory explains common observations of the orders of magnitude of liquid water content in convective and stratiform clouds. Finally, sensitivity tests of the numerically integrated theoretical equations are documented with respect to variations in cloud condensation nucleus (CCN) aerosols and updraft speed. In conclusion, it is shown that this theory of in-cloud activation, with an increasing supersaturation during ascent, applies to both ice-only and liquid-only cloud.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

CGOLS V: Disk-wide Stellar Feedback and Observational Implications of the Cholla Galactic Wind Model

Abstract We present the fifth simulation in the Cholla Galactic OutfLow Simulation (CGOLS) project—a set of isolated starburst galaxy simulations modeled over large scales (10 kpc) at uniformly high resolution (Δx≈ 5 pc). Supernova feedback in this simulation is implemented as a disk-wide distribution of clusters, and we assess the impact of this geometry on several features of the resulting outflow, including the radial profiles of various phases; mass, momentum, and energy outflow rates; covering fraction of cool gas; mock absorption-line spectra; and X-ray surface brightness. In general, we find that the outflow generated by this model is cooler, slower, and contains more mass in the cool phase than a more centrally concentrated outflow driven by a similar number of supernovae. In addition, the energy loading factors in the hot phase are an order of magnitude lower, indicating much larger losses due to radiative cooling in the outflow. However, coupling between the hot and cool phases is more efficient than in the nuclear burst case, with almost 50% of the total outflowing energy flux carried by the cool phase at a radial distance of 5 kpc. These physical differences have corresponding signatures in observable quantities: the covering fraction of cool gas is much larger, and there is greater evidence of absorption in low and intermediate ionization energy lines. Taken together, our simulations indicate that centrally concentrated starbursts are more effective at driving hot, low-density outflows that will expand far into the halo, while galaxy-wide bursts may be more effective at removing cool gas from the disk.

Astronomy & Astrophysics↗
DOE OSTI2024

Modeling the Far-infrared Polarization Spectrum of a High-mass Star-forming Cloud

The polarization spectrum, or wavelength dependence of the polarization fraction, of interstellar dust emission provides important insights into the grain alignment mechanism of interstellar dust grains. We investigate the far-infrared polarization spectrum of a realistic simulated high-mass star-forming cloud under various models of grain alignment and emission. We find that neither a homogeneous grain alignment model nor a grain alignment model that includes collisional dealignment is able to produce the falling spectrum seen in observations. On the other hand, we find that a grain alignment model with grain alignment efficiency dependent on local temperature is capable of producing a falling spectrum that is in qualitative agreement with observations of OMC-1. For the model most in agreement with OMC-1, we find no correlation between the temperature and the slope of the polarization spectrum. However, we do find a positive correlation between the column density and the slope of the polarization spectrum. We suggest this latter correlation to be the result of wavelength-dependent polarization by absorption.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Multiphysics Computational-Fluid-Dynamics (CFD) for Design and Scale-Up of Gas Bioreactors that Utilize CO2

Gas fermentation technology offers sustainable and high carbon-efficiency routes to fuels and chemicals. However, efficiently delivering low-solubility substrate gases to production-scale bioreactors is a significant technical challenge that could limit productivity. We perform fundamental and applied multiphysics computational fluid dynamics (CFD) research targeting specific challenges of gas delivery in fermentation systems that utilize varied gas-compositions, for e.g. CO2/CO/CH4/H2 substrates: bubble dynamics, coupled mass-transfer and reaction, that can lead to optimal reactor designs at scale. This work will support BETO goals towards greenhouse gas reduction, derisking technologies toward commercialization/deployment and sustainable-aviation-fuel synthesis targets.

BIOMASS FUELS↗
DOE OSTI2024

Blade and Rim Seal Design of a First Stage High Pressure Turbine for a 300 MWe Supercritical CO2 Power Cycle

A first stage high-pressure turbine (HPT) blade is optimized for a 300 MWe supercritical CO2 (sCO2) power cycle using the surrogate-assisted genetic algorithm optimizer in Numeca FINE/Design 3D with objectives of increasing efficiency and decreasing heat load to the blade. The National Institute of Standards and Technology Reference Fluid Thermodynamic and Transport Properties Database (NIST REFPROP) [1] data for supercritical CO2 is formatted into tables of bicubic polynomial coefficients for use in condensable gas simulations in FINE/Turbo. Nearly 3000 unique shapes are evaluated via three-dimensional Reynolds Averaged Navier Stokes simulations, yielding increases in efficiency of up to 0.85 percentage points and decreases in heat load of 14%. A final blade, deemed the advanced blade, is chosen for future experimental analysis. Following this, a squealer tip optimization is performed on both the baseline and advanced blade designs. This optimization resulted in a performance gain of 1.25 points in efficiency and 15% reduction in tip heat load compared to the baseline flat tip design at the same clearance. In tandem, an optimization of the rotor-stator platform rim seal is performed using a parametrized geometry allowing for straight, meandering, and knife seal cavities. This multi-objective optimization focuses on decreasing the cooling mass flow and increasing the heat flux from the rotor and stator disk. The optimization resulted in cooling mass flow decreases of up to 26% while maintaining the average heat flux on the rim seal.

Tuite, Logan↗
DOE OSTI2022

Low temperature upcycling of polyethylene to gasoline range chemicals: Hydrogen transfer and heat compensation to endothermic pyrolysis reaction over zeolites

Selective production of gasoline ranged chemicals were of great interest in the field of plastic upcycling. Here this work reports exothermic hydrogen transfer reaction which was observed when HY zeolite was adopted to catalytic pyrolyze the polyethylene to gasoline ranged chemicals, while it was not observed when H-ZSM5 was used as catalyst. Both zeolite catalysts could significantly bring down the reaction temperature from 500 to 300–350 °C. TG-FITR analysis revealed that products obtained with HY zeolites were dominated with saturated hydrocarbons as compared to H-ZSM5 where the combination of alkanes, alkenes, and aromatics was obtained. In addition to the formation of saturated compounds, the TG-DSC analysis confirmed that, over the HY zeolites, the endothermic hydrogen transfer reaction of olefins occurred along with the pyrolysis of LDPE visibly when the zeolite ratio in the zeolite/polyethylene mixture exceeded 50% by mass. The TG results also indicated that the polyethylene undergone nearly 100% converted with very few residues. Further product analysis from batch pyrolysis by GC-MS confirmed that gasoline ranged iso-alkanes were produced over HY zeolite. This study highlighted that coupling exothermic hydrogen transfer reactions with endothermic pyrolysis could be an energy-efficient way of producing gasoline ranged chemicals. Chemical upcycling of plastics is tunable by using different zeolite combinations for the formation of desired products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Predicting the structural basis of targeted protein degradation by integrating molecular dynamics simulations with structural mass spectrometry

Targeted protein degradation (TPD) is a promising approach in drug discovery for degrading proteins implicated in diseases. A key step in this process is the formation of a ternary complex where a heterobifunctional molecule induces proximity of an E3 ligase to a protein of interest (POI), thus facilitating ubiquitin transfer to the POI. In this work, we characterize 3 steps in the TPD process. (1) We simulate the ternary complex formation of SMARCA2 bromodomain and VHL E3 ligase by combining hydrogen-deuterium exchange mass spectrometry with weighted ensemble molecular dynamics (MD). (2) We characterize the conformational heterogeneity of the ternary complex using Hamiltonian replica exchange simulations and small-angle X-ray scattering. (3) We assess the ubiquitination of the POI in the context of the full Cullin-RING Ligase, confirming experimental ubiquitinomics results. Differences in degradation efficiency can be explained by the proximity of lysine residues on the POI relative to ubiquitin.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Solventless, Ambient-Pressure Production of Bio-Based Lactones Over Earth-Abundant, Mixed Metal Oxide Catalysts for Circular Polyesters

Transitioning to a circular plastics economy will require use of renewable feedstocks, energy-efficient processes, and closed-loop recyclable polymers, such as polyesters. A key challenge lies in sustainably sourcing monomers used to make recyclable polyesters. This work presents a catalytic platform utilizing earth-abundant Cu(x)Ca(1-x)O mixed metal oxides for the oxidative dehydrocyclization of bio-based diols to lactones, which are advantaged for energy-efficient ring-opening polymerization. Operating below 200 degrees C, at ambient pressure, and without solvent, the process uses air as the sole oxidant, achieving high yields of lactones across a broad substrate scope of C4-8 diols in the liquid phase. The oxidative dehydrocyclization reaction is thermodynamically downhill due to water formation and energy-efficient compared to incumbent, non-redox pathways utilized in fossil carbon-based industrial processes for lactone production. Mechanistic studies reveal facile redox cycling of Cu2+-O(Ca2+)-Cu2+ interfacial sites unique to the developed catalyst. Techno-economic analysis and life cycle assessment estimate 40% lower energy demand and 15% lower GHG intensity per mass of butyrolactone produced compared to the fossil carbon-based route. Liquid-phase oxidative dehydrocyclization offers a promising approach for scalable lactone production from renewable, bio-based diols to enable circular polyesters.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Advanced manufacturing for electrosynthesis of fuels and chemicals from CO 2

Advanced manufacturing (AM) represents an appealing approach for creating novel electrochemical systems for chemicals synthesis. In this work, we demonstrate AM for rapid development and testing for improved performance for the carbon dioxide reduction reaction across an evolution of vapor-fed reactor designs. In our final design, we observe activation- and mixed-control regimes for a variety of operating conditions via inlet CO 2 flow rate and electrochemical potential. Furthermore, we define a dimensionless number (Da) to identify mass transport regimes by exploring the impact of hypothesized underlying mass transport mechanisms, including consumption of CO 2 via OH - , increased local temperatures, and partial penetration of electrolyte into gas diffusion layer. The accelerated pace of reactor design and development led to high geometric current densities (500 mA cm -2 ), heightened selectivity (85.5% FE C 2+ products), and increased carbon dioxide conversion (16.6%) and cathodic energy efficiency (49.6% CO 2 R). Using AM vapor-fed reactors, we attain high ethylene (3.67%) and record ethanol (3.66%) yields compared to the literature. Finally, this work underscores the promise of AM for accelerating reactor design, understanding of governing phenomena, and improving the performance of catalytic systems.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Data from: "Growth strategies and threshold responses to water deficit modulate effects of warming on tree seedlings from forest to alpine"

This data package contains data that were used to support conclusions drawn in “Growth strategies and threshold responses to water deficit modulate effects of warming on tree seedlings from forest to alpine”, by Lazarus, Castanha et al. 2017. Data were collected at field sites within the Alpine Treeline Warming Experiment (ATWE) on Niwot Ridge, Colorado, USA, and at the U.S. Geological Survey laboratory located in Boise, Idaho. This archive contains comma-separated-values (.csv) files, as well as the same files in Microsoft Excel (.xlsx) format, which can be opened by either Microsoft Excel, R, or any simple text editor program. There are two types of geospatial data files: .kml and ESRI shapefiles (.shp). The kml files contain placemarks, which can be opened by Google Earth, or Google Maps. The ESRI shapefiles can be opened by any geographic information system application that can read shapefiles, including ESRI's entire ArcGIS suite, and QGIS. We asked whether and how tree species differences in response to water deficit relates to their establishment along the gradient from forest to alpine. To do this, we compared growth and moisture stress responses in first-year seedlings of three species planted in common gardens subject to a factorial of heating and watering treatments below, at, and above tree line. This combination of an elevation gradient alongside warming and watering treatments enabled us to observe species differences in seedling responses to a broad set of climatic conditions.Entire seedlings were harvested at c. 3- and again at 9 weeks of age following germination/emergence in the experimental plots, and we then measured dry mass (DM) of above and belowground parts, root length, root mass fraction (RMF), relative growth rates (RGRs) from seed to 3 weeks and from 3 to 9 weeks, turgor-loss point (TLP), and photosynthetic WUE (as δ13C). Also included in this dataset (but not described in the manuscript) are measures of specific leaf area (SLA) and other variables generated by pressure-volume curves (saturated water content, osmotic potential at full turgor, elastic modulus).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Production of ice-nucleating particles (INPs) by fast-growing phytoplankton

Sea spray aerosol contains ice-nucleating particles (INPs), which affect the formation and proper ties of clouds. Here, we show that aerosols emitted from fast-growing marine phytoplankton produce effective immersion INPs, which nucleate at temperatures significantly warmer than the atmospheric homogeneous freezing (-38.0 °C) of pure water. Aerosol sampled over phytoplankton cultures grown in a Marine Aerosol Ref erence Tank (MART) induced nucleation and freezing at temperatures as high as -15.0 °C during exponential phytoplankton growth. This was observed in monospecific cultures representative of two major groups of phy toplankton, namely a cyanobacterium (Synechococcus elongatus) and a diatom (Thalassiosira weissflogii). Ice nucleation occurred at colder temperatures (-28.5 °C and below), which were not different from the freezing temperatures of procedural blanks, when the cultures were in the stationary or death phases of growth. Ice nucleation at warmer temperatures was associated with relatively high values of the maximum quantum yield of photosystem II ( Φ PSII ), an indicator of the physiological status of phytoplankton. High values of Φ PSII indicate the presence of cells with efficient photochemistry and greater potential for photosynthesis. For comparison, field measurements in the North Atlantic Ocean showed that high net growth rates of natural phytoplankton assemblages were associated with marine aerosol that acted as effective immersion INPs at relatively warm temperatures. Data were collected over 4 d at a sampling station maintained in the same water mass as the water column stabilized after deep mixing by a storm. Phytoplankton biomass and net phytoplankton growth rate (0.56 d -1 ) were greatest over the 24 h preceding the warmest mean ice nucleation temperature (-25.5 °C). Collectively, our laboratory and field observations indicate that phytoplankton physiological status is a useful predictor of effective INPs and more reliable than biomass or taxonomic affiliation. Ocean regions associated with fast phytoplankton growth, such as the North Atlantic during the annual spring bloom, may be significant sources of atmospheric INPs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Application of a Coincidence Ring Ratio Moderator Correction to the Assay of 235U Residues

Processing of irradiated UAl targets by NaOH dissolution for the extraction of 99Mo results in the creation of high-activity highly enriched uranium (HEU)–bearing residues that must be quantified. The HEU residues generated from this process are assayed using an Active Well Coincidence Counter (AWCC) that has been modified to accommodate >1 Sv/h gamma-ray exposure rates to provide a 235U mass value for each residues container. The HEU residues include a significant amount of residual moderator from the dissolution process. Fission product decay heat drives off much—but not all—of the hydrogen from the dissolution, leaving an unknown moderator content in the residues. The moderator content impacts the induced fission rate in the HEU, detection efficiency, and die-away time of the emitted neutrons and requires implementation of a moderator correction factor. Three moderator correction techniques have been implemented: an active coincidence ring ratio method, a conventional 252Cf Add-A-Source (AAS) measurement, and an AAS ring ratio measurement. The 252Cf AAS and the AAS ring ratio methods are potentially much faster, but they require additional sample handling and precise positioning of the residues container and the 252Cf source. This study was performed using a combination of Monte Carlo N-Particle (MCNP) [1] simulation and measurements. The impact of the moderator content on the AWCC measurement and the relative performance of the three moderator correction methods are presented.

Mcelroy Jr, Robert↗
DOE OSTI2019

How to optimally constrain galaxy assembly bias: supplement projected correlation functions with count-in-cells statistics

Most models for the statistical connection between galaxies and their haloes ignore the possibility that galaxy properties may be correlated with halo properties other than halo mass, a phenomenon known as galaxy assembly bias. And yet, it is known that such correlations can lead to systematic errors in the interpretation of survey data that are analysed using traditional halo occupation models. At present, the degree to which galaxy assembly bias may be present in the real Universe, and the best strategies for constraining it remain uncertain. We study the ability of several observables to constrain galaxy assembly bias from redshift survey data using the decorated halo occupation distribution (dHOD), an empirical model of the galaxy-halo connection that incorporates assembly bias. We cover an expansive set of observables, including the projected two-point correlation function w p ( r p ), the galaxy-galaxy lensing signal ΔΣ( r p ), the void probability function VPF( r ), the distributions of counts-in-cylinders P(NCIC), and counts-in-annuli P(NCIA), and the distribution of the ratio of counts in cylinders of different sizes P ( N 2 /N 5 ). We find that despite the frequent use of the combination w p ( r p ) + ΔΣ( r p ) in interpreting galaxy data, the count statistics, P ( N CIC ) and P ( N CIA ), are generally more efficient in constraining galaxy assembly bias when combined with w p ( r p ). Constraints based upon w p ( r p ) and ΔΣ(rp) share common degeneracy directions in the parameter space, while combinations of r p w p ( r p ) with the count statistics are more complementary. Therefore, we strongly suggest that count statistics should be used to complement the canonical observables in future studies of the galaxy-halo connection.

galaxies: evolution↗
DOE OSTI2026

Parallel-in-Time Solution of Allen-Cahn Equations by Integrating Operator Learning into the Parareal Method

While recent advances in deep learning have shown promising efficiency gains in solving time-dependent partial differential equations (PDEs), matching the accuracy of conventional numerical solvers still remains a challenge. One strategy to improve the accuracy of deep learning-based solutions for time-dependent PDEs is to use the learned model as the coarse propagator in the Parareal method and a traditional numerical method as the fine solver. However, successful integration of deep learning into the Parareal method requires consistency between the coarse and fine solvers, particularly for PDEs exhibiting rapid changes such as sharp transitions. Here, to ensure this consistency, we propose using convolutional neural networks (CNNs) to learn the fully discrete time-stepping operator defined by the same numerical scheme employed as the fine solver. We demonstrate the effectiveness of the proposed method in solving the classical and mass-conservative Allen–Cahn (AC) equations. Through iterative updates in the Parareal algorithm, our approach achieves a significant computational speedup compared to traditional fine solvers while converging to high-accuracy solutions. Our results highlight that the proposed hybrid Parareal algorithm effectively accelerates simulations, particularly when implemented on multiple GPUs, and converges to the desired accuracy in only a few iterations. Another advantage of our method is that the CNN model is trained on trajectory-based data generated from random initial conditions, such that the trained model can be used to solve the AC equations with various initial conditions without retraining. This work demonstrates the potential of integrating neural network methods into parallel-in-time frameworks for efficient and accurate simulations of time-dependent PDEs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Enhanced Reversibility of Iron Metal Anode with a Solid Electrolyte Interphase in Concentrated Chloride Electrolytes

Iron is a promising candidate for a cost-effective anode for large-scale energy storage systems due to its natural abundance and well-established mass production. Recently, Fe-ion batteries (FeIBs) that use ferrous ions as the charge carrier have emerged as a potential storage solution. The electrolytes in FeIBs are necessarily acidic to render the ferrous ions more anodically stable, allowing a wide operation voltage window. However, the iron anode suffers severe hydrogen evolution reaction with a low Coulombic efficiency (CE) in an acidic environment, shortening the battery cycle life. Herein, a hybrid aqueous electrolyte that forms a solid-electrolyte interphase (SEI) layer on the Fe anode surface is introduced. The electrolyte mainly comprises FeCl 2 and ZnCl 2 as cosalts, where the Zn-Cl anionic complex species of the concentrated ZnCl 2 allows dimethyl carbonate (DMC) to be miscible with the aqueous ferrous electrolyte. SEI derived from DMC's decomposition passivates the iron surface, which leads to an average CE of 98.3% and much-improved cycling stability. As a result, this advancement shows the promise of efficient and durable FeIBs.

25 ENERGY STORAGE↗
DOE OSTI2020

Enhancing Chemical Stability and Suppressing Ion Migration in CH 3 NH 3 PbI 3 Perovskite Solar Cells via Direct Backbone Attachment of Polyesters on Grain Boundaries

Organic–inorganic halide perovskites feature excellent optoelectronic properties but poor chemical stability. While passivating perovskite grain boundary (GB) by polymers shows prospects on long-term performance of perovskite solar cells (PSCs), its detailed impact on the ion migration phenomenon, which largely deteriorates the PSC stability, remains less probed. In this work, we introduce a new polar polymer, polycaprolactone (PCL), to passivate GBs of methylammonium lead triiodide (MAPbI 3 ) perovskite with only 1–2 polymer monolayers via direct backbone attachment. The PSCs with passivated MAPbI 3 , using a classic but less stable Spiro-OMeTAD (2,2',7,7'-tetrakis[N,N-di(4-methoxyphenyl)amino]-9,9'-spirobifluorene) hole transport layer (HTL), exhibit improved power conversion efficiencies up to 20.1%, with 90% of the initial PCE being preserved after 400 h ambient storage, and 80% even after 100 h, 85 °C aging. The improved PSC stability indicates critical roles of PCL GB passivation in retarding moisture-induced decomposition and suppressing ion migration within the perovskite. Furthermore, time-of-flight secondary ion mass spectrometry reveals that I– ions can actively migrate into the electrode, HTL, and their interface in nonpassivated PSCs, even without an externally applied electric field, while such migration is significantly mitigated in PCL-passivated PSCs. This effective GB passivation by PCL suggests an important potential of polymer additives toward the development of stable high-performance PSCs.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Development of Heterogeneous Ice Nucleation Rate Coefficient Parameterizations From Ambient Measurements

Ice nucleating particles (INPs) are a rare subset of particles that can have an outsized impact relative to their prevalence. To simulate INP variability, models require parameterizations for the most important sources of INPs. Most parameterizations in the literature were developed from laboratory experiments that used proxies for ambient particles. Whether these laboratory models effectively represent ambient aerosol is still not well understood and parameterizations developed from field measurements may be more atmospherically relevant. Expanding on previous work in which we used an ice chamber and a single-particle mass spectrometer (SPMS) to characterize INP composition, we calculate heterogeneous ice nucleation rate coefficients for ambient particles. We find good agreement between our dust and previous measurements of airborne dust. We also use a Monte Carlo approach to assess the relative contribution of each measurement to the uncertainty and find that the biggest source is the sampling efficiency of the SPMS.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Experimental investigation of laser ablation of stone polycrystalline targets

We report the results of an experimental investigation of ablation of stone polycrystalline targets of complex multicomponent composition, which imitate the substance of asteroids. The targets were irradiated by nanosecond pulses of a neodymium laser at an energy density Φ{sub L} of up to 5 × 10{sup 4} J cm{sup −2}. The experiments demonstrated the existence of two ablation regimes, with the boundary between them lying at Φ{sub L} ≈ 4000 J cm{sup −2}. The regime change is characterised by a change in the form of the dependence of the surface mass density of removed target material on the laser energy density and by the appearance of a minimum in the dependence of specific energy of destruction on Φ{sub L}. This is supposedly related to the passage from a one-dimensional plasma plume expansion to the three-dimensional one and the corresponding decrease in the efficiency of energy transfer from the laser beam to the target due to a lowering of laser-produced plasma density. Our experiments also showed the existence of a maximum in impulse coupling coefficient C{sub m} as a function of laser energy density (C{sub m} ≈ 6.3 × 10{sup −5} N W{sup −1} for Φ{sub L} = Φ{sub opt} ≈ 25 J cm{sup −2}). Maxima were also recorded in the dependences of the ablation efficiency and average ablation flow velocity on Φ{sub L}. For Φ{sub L} > Φ{sub opt}, the decrease in the function C{sub m}(Φ{sub L}) turns out to be much steeper than for metals and polymer materials. The difference is supposedly due to the lower strength and lower plasticity of the polycrystalline stone targets. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗