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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 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Additive Manufactured Composite Phase-Change Material for Thermal Energy Storage Applications

Phase-change materials play a critical role in industrial energy storage applications to drive efficiency improvements, thermal energy management, and carbon emissions reductions. Recently, it has been shown that rapid solidification of alloys with metastable immiscibility in the liquid phase has the potential to form unique microstructures in which a low-melting phase is uniformly distributed in a high-melting matrix. This feature can be exploited using additive manufacturing to produce components with complex geometries containing such unique phase-change microstructures. Phase-field simulations utilizing high-performance computing were used to provide a detailed description of the evolution of the active phase during service in terms of their morphology and composition in different polycrystalline matrix grain morphologies that are typically produced during additive manufacturing. Phase field simulations were performed using, MEUMAPPS-SL (Microstructure Evolution Using Massively Parallel Phase-field Simulations – Solid Liquid) code that was developed in-house by the Oak Ridge National Laboratory. The simulations utilized the capabilities of the Kestrel supercomputer at the National Renewable Energy Laboratory. The simulation results were compared with experimental results generated at Siemens Energy, Inc. The results indicate that the kinetics of liquid spreading along grain boundaries is largely determined by the mobility of the triple line along the intersection of the grain boundary liquid and the grain boundary plane.

25 ENERGY STORAGE↗
DOE OSTI2014

An analytical model to predict curvature effects of the carbon nanotube on the overall behavior of nanocomposites

In this study, analytical expressions are introduced to provide a better understanding of carbon nanotubes (CNTs) curvature on the overall behavior of nanocomposites. The curviness of CNT is modeled as the wave geometries, and the transformed physical characteristics are applied to micromechanical framework. Since five independent elastic constants of CNTs are essential to derive the waviness effect, atomistic molecular statics simulations with varying nanotube radii are conducted. Influences of CNT curviness on the effective stiffness of the nanocomposites are analyzed, noting that the curvature effect is significantly influential on the effective stiffness of the nanocomposites, and it may improve or reduce the reinforcing effect depending on the orientation of CNTs. In addition, the predictions are compared with experimental data of the CNT-reinforced nanocomposites to assess the reliability of the proposed method. The developed constitutive model is expected to be used to determine the volume concentration of the reinforcing CNTs and mechanical responses of CNT-reinforced composites under various CNT curvature, radius, and orientation conditions.

42 ENGINEERING↗
DOE OSTI2019

A New Efficient Quantitative Multi-component Phase Field: Lattice Boltzmann Model for Simulating Ti6Al4V Solidified Dendrite Under Forced Flow

Ti6Al4V is a widely used, multi-component alloy in additive manufacturing, during which the fluid flow in the molten pool significantly affects the solidified dendrites. To predict and further control the microstructure, modeling and simulating the microstructure evolution play a critical role. In this study, a newly developed, efficient, quantitative multi-component phase-field (PF) model is coupled with a lattice Boltzmann (LB) model to simulate Ti6Al4V solidified dendrite evolution under fluid flow. The accuracy and convergence behavior of the model is validated by the Gibbs–Thomson relation at the dendrite tip. Single and multiple two-dimensional (2D) equiaxed dendrite evolution cases under forced flow were simulated. Results show that the dendrite pattern is influenced remarkably by the fluid flow. Underlying mechanisms of the asymmetrical evolution are revealed by discussing the interaction among the flow, composition distribution and dendrite morphology, quantitatively. The dendrite kinetics are also derived, which ascertains the relationship between tip velocity and undercooling and inlet velocity and is the foundation for larger-scale simulation. We believe that the coupled quantitative multi-component PF–LB framework employed in this study helps in investigating the solidified dendrite morphology evolution in a deep and quantitate manner.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Tropospheric aerosols over the western North Atlantic Ocean during the winter and summer deployments of ACTIVATE 2020: life cycle, transport, and distribution

The Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) is a NASA mission to characterize aerosol–cloud interactions over the western North Atlantic Ocean (WNAO). Such characterization requires understanding of life cycle, composition, transport pathways, and distribution of aerosols over the WNAO. This study uses the GEOS-Chem model to simulate aerosol distributions and properties that are evaluated against aircraft, ground-based, and satellite observations during the winter and summer field deployments in 2020 of ACTIVATE. Transport in the boundary layer (BL) behind cold fronts was a major mechanism for the North American continental outflow of pollution to the WNAO in winter. Turbulent mixing was the main driver for the upward transport of sea salt within and ventilation out of BL in winter. The BL aerosol composition was dominated by sea salt, which increased in the summer, followed by organics and sulfate. Aircraft in situ aerosol measurements provided useful constraints on wet scavenging in GEOS-Chem. The model generally captured observed features such as continental outflow, land–ocean gradient, and mixing of anthropogenic aerosols with sea salt. Model sensitivity experiments with elevated smoke injection heights to the mid-troposphere (versus within BL) better reproduced observations of smoke aerosols from the western US wildfires over the WNAO in the summer. Model analysis suggests strong hygroscopic growth of sea salt particles and their seeding of marine BL clouds over the WNAO (< 35° N). Future modeling efforts should focus on improving parameterizations for aerosol wet scavenging, implementing realistic smoke injection heights, and applying high-resolution models that better resolve vertical transport.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Machine learning prediction on the fractional free volume of polymer membranes

Fractional free volume (FFV) characterizes the microstructural level features of polymers and affects their properties including thermal, mechanical, and separation performance. Experimental measurements and theoretical analyses have been used to quantify the FFV of polymers, but challenges remain because of their limitations. Experimental measurements are laborious and based on semi empirical equations, while Bondi’s group contribution theory involves ambiguities like the determination of van der Waals volume and the choice of factor values in the theoretical equation. To efficiently evaluate the FFV of polymers, this study utilizes high-throughput molecular dynamics (MD) simulations to build a large dataset regarding polymer’s FFV. Based on this large dataset, we further build machine learning (ML) models to establish the composition-structure relation. Inspired by group contribution theory which correlates polymer’s functional groups to FFV, our ML models correlate polymer’s substructures or physico-chemical indexes to FFV. Here, our study first benchmarks the MD simulation protocol to obtain reliable FFV of polymers and then carries out high-throughput MD simulations for more than 6,500 homopolymers and 1,400 polyamides. Such a large and diverse dataset makes the well-trained ML models more generalizable, compared with the group contribution theory. The efficiency of a feed forward neural network model is further demonstrated by applying it to a hypothetical polyimide dataset of more than 8 million chemical structures. The predicted FFVs of hypothetical polyimides are further validated by MD simulations. The obtained FFVs of the 8 million polymers, plus their previously reported gas separation performances, demonstrate the promising capability of ML virtual screening for the discovery of polymer membranes with exceptional permeability/selectivity.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Homogeneous states in driven granular mixtures: Enskog kinetic theory versus molecular dynamics simulations

The homogeneous state of a binary mixture of smooth inelastic hard disks or spheres is analyzed. The mixture is driven by a thermostat composed by two terms: a stochastic force and a drag force proportional to the particle velocity. The combined action of both forces attempts to model the interaction of the mixture with a bath or surrounding fluid. The problem is studied by means of two independent and complementary routes. First, the Enskog kinetic equation with a Fokker-Planck term describing interactions of particles with thermostat is derived. Then, a scaling solution to the Enskog kinetic equation is proposed where the dependence of the scaled distributions φ{sub i} of each species on the granular temperature occurs not only through the dimensionless velocity c = v/v{sub 0} (v{sub 0} being the thermal velocity) but also through the dimensionless driving force parameters. Approximate forms for φ{sub i} are constructed by considering the leading order in a Sonine polynomial expansion. The ratio of kinetic temperatures T{sub 1}/T{sub 2} and the fourth-degree velocity moments λ{sub 1} and λ{sub 2} (which measure non-Gaussian properties of φ{sub 1} and φ{sub 2}, respectively) are explicitly determined as a function of the mass ratio, size ratio, composition, density, and coefficients of restitution. Second, to assess the reliability of the theoretical results, molecular dynamics simulations of a binary granular mixture of spheres are performed for two values of the coefficient of restitution (α = 0.9 and 0.8) and three different solid volume fractions (ϕ = 0.00785, 0.1, and 0.2). Comparison between kinetic theory and computer simulations for the temperature ratio shows excellent agreement, even for moderate densities and strong dissipation. In the case of the cumulants λ{sub 1} and λ{sub 2}, good agreement is found for the lower densities although significant discrepancies between theory and simulation are observed with increasing density.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Topological origin of phase separation in hydrated gels

Depending on their composition, hydrated gels can be homogeneous or phase-separated, which, in turn, affects their dynamical and mechanical properties. However, the nature of the structural features, if any, that govern the propensity for a given gel to phase-separate remains largely unknown. Here, we argue that the propensity for hydrated gels to phase-separate is topological in nature. We employ reactive molecular dynamics simulations to model the early-age precipitation of calcium–alumino–silicate–hydrate (Csingle bondAsingle bondSsingle bondH) gels with varying compositions, i.e., (CaO) 1.7 (Al 2 O 3 ) x (SiO 2 ) 1 – x (H 2 O) 3.7 + x . By adopting topological constraint theory, we investigate the structural origin of phase separation in hydrated gels. We report the existence of a homogeneous-to-phase-separated transition, wherein Si-rich (x ≤ 0.10) Csingle bondAsingle bondSsingle bondH gels are homogeneous, whereas Al-rich (x > 0.10) Csingle bondAsingle bondSsingle bondH gels tend to phase-separate. Furthermore, we demonstrate that this transition is correlated to a topological flexible-to-rigid transition within the atomic network. Finally, we reveal that the propensity for topologically-overconstrained gels to phase-separate arises from the existence of some internal stress within their atomic network, which acts as an energy penalty that drives phase separation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Scaling Field-Theoretic Simulation for Multicomponent Mixtures with Neural Operators

Multicomponent polymer mixtures are ubiquitous in biological self-organization but are notoriously difficult to study computationally. Plagued by both slow single molecule relaxation times and slow equilibration within dense mixtures, molecular dynamics simulations are typically infeasible at the spatial scales required to study the stability of mesophase structure. Polymer field theories offer an attractive alternative, but analytical calculations are only tractable for mean-field theories and nearby perturbations, constraints that become especially problematic for fluctuation-induced effects such as coacervation. Here, we show that a recently developed technique for obtaining numerical solutions to partial differential equations based on operator learning, neural operators, lends itself to a highly scalable training strategy by parallelizing per-species operator maps. We illustrate the efficacy of our approach on six-component mixtures with randomly selected compositions and that it significantly outperforms the state-of-the-art pseudospectral integrators for field-theoretic simulations, especially as polymer lengths become long.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Heterogeneous chain dynamics and aggregate lifetimes in precise acid-containing polyethylenes: Experiments and simulations

Melt state dynamics for a series of strictly linear polyethylenes with precisely spaced associating functional groups were investigated. The periodic pendant acrylic acid groups form hydrogen-bonded acid aggregates within the polyethylene (PE) matrix. The dynamics of these nanoscale heterogeneous morphologies were investigated from picosecond to nanosecond timescales by both quasi-elastic neutron scattering (QENS) measurements and fully atomistic molecular dynamics (MD) simulations. Two dynamic processes were observed. The faster dynamic processes which occur at the picosecond timescales are compositionally insensitive and indicative of spatially restricted local motions. The slower dynamic processes are highly composition dependent and indicate the structural relaxation of the polymer backbone. Higher acid contents, or shorter PE spacers between pendant acid groups, slow the structural relaxation timescale and increase the stretching parameter (β) of the structural relaxation. Additionally, the dynamics of specific hydrogen atom positions along the backbone correlate structural heterogeneity imposed by the associating acid groups with a mobility gradient along the polymer backbone. At time intervals (<2 ns), the mean-squared displacements for the four methylene groups closest to the acid groups are up to 10 times smaller than those of methylene groups further from the acid groups. At longer timescales acid aggregates rearrange and the chain dynamics of the slow, near-aggregate regions and the faster bridge regions converge, implying a characteristic timescale for the passage of chains between aggregates. As a result, the characterization of the nanoscale chain dynamics in these associating polymer systems both provides validation of simulation force fields and provides understanding of heterogeneous chain dynamics in associating polymers.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Dynamics of plasma atomic layer etching: Molecular dynamics simulations and optical emission spectroscopy

Atomic layer etching is intrinsically dynamic as it involves sequential and repeated exposures of a surface to be etched with different species at different energies. The composition and structure of the near surface region change in both time and depth. Full understanding of this process requires resolving both temporal and spatial variations. In this work, we consider silicon (Si) atomic layer etching (ALE) by alternating exposure to chlorine gas (Cl 2 ) and argon ions (Ar + ). Molecular dynamics (MD) simulations are compared to experimental measurements with the aim of better understanding the dynamics of ALE and to test the simulation procedure. The simulations help to more fully interpret the experimental measurements. Further, optical emission measured just above the surface being etched can be related to etch products and can, therefore, be directly compared to simulation predictions. The simulations capture the measured initial product distribution leaving the surface and match the measured etch per cycle reasonably well. While simulations demonstrate the importance of ion-induced surface damage and mixing into a layer below the surface, the depth of which depends mainly on ion energy, the experiments suggest there is more Cl mixed into the layer than the MD procedure predicts.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2014

Controls of Wellbore Flow Regimes on Pump Effluent Composition

Where well water and formation water are compositionally different or heterogeneous, pump effluent composition will vary due to partial mixing and transport induced by pumping. Investigating influences of purging and sampling methodology on composition variability requires quantification of wellbore flow regimes and mixing. As a basis for this quantification, analytical models simulating Poiseuille flow were developed to calculate flow paths and travel times. Finite element modeling was used to incorporate influences of mixing. Parabolic velocity distributions within the screened interval accelerate with cumulative inflow approaching the pump intake while an annulus of inflowing formation water contracts uniformly to displace an axial cylinder of pre-pumping well water as pumping proceeds. Increased dispersive mixing forms a more diffuse formation water annulus and the contribution of formation water to pump effluent increases more rapidly. Models incorporating viscous flow and diffusion scale mixing show that initially pump effluent is predominantly pre-pumping well water and compositions vary most rapidly. After two screen volumes of pumping, 94% of pump effluent is inflowing formation water. Where the composition of formation water and pre-pumping well water are likely to be similar, pump effluent compositions will not vary significantly and may be collected during early purging or with passive sampling. However, where these compositions are expected to be considerably different or heterogeneous, compositions would be most variable during early pumping, that is, when samples are collected during low-flow sampling. Purging of two screen volumes would be required to stabilize the content and collect a sample consisting of 94% formation water.

58 GEOSCIENCES↗
DOE OSTI2023

Insights into Waterflooding in Hydrocarbon-Bearing Nanochannels of Varying Cross Sections from Mesoscopic Multiphase Flow Simulations

Waterflooding is one of the geotechnique used to recover fuel sources from nanoporous geological formations. The scientific understanding of the process that involves the multiphase flow of nanoconfined fluids, however, has lagged, mainly due to the complex nanopore geometries and chemical compositions. To enable benchmarked flow of nanoconfined fluids, the architected geomaterials, such as synthesized mesoporous silica with tunable pore shapes and surface chemical properties, are used for designing and conducting experiments and simulations. This work uses a modified many-body dissipative particle dynamics (mDPD) model with accurately calibrated parameters to perform parametric flow simulations for studying the influences of waterflooding driven power, pore shape, surface roughness, and surface wettability on the multiphase flow in heptane-saturated silica nanochannels. Remarkably, up to 80\% reduction in the effective permeability is found for water-driven heptane flow in a baseline 4.5 nm-wide slit channel, when compared with the Hagen–Poiseuille equation. In the 4.5 nm-wide channels with architected surface roughness, the flow rate is found either higher or lower than the baseline case, depending on the shape and size of cross-sections. High wettability of the solid surface to water is essential for achieving high recovery of heptane, regardless of surface roughness. When the solid surface is less wetting or non-wetting to water, the existence of an optimal waterflooding driven power is found to allow for the highest possible recovery. A detailed analysis on the evolution of the transient water-heptane interface in those nanochannels is presented to elucidate the underlying mechanisms that impact or dictate the multiphase flow behaviors.

58 GEOSCIENCES↗
DOE OSTI2016

Conductive network formation of carbon nanotubes in elastic polymer microfibers and its effect on the electrical conductance: Experiment and simulation

We investigate how the electrical conductance of microfibers (made of polymers and conductive nanofillers) decreases upon uniaxial deformation by performing both experiments and simulations. Even though various elastic conductors have been developed due to promising applications for deformable electronic devices, the mechanism at a molecular level for electrical conductance change has remained elusive. Previous studies proposed that the decrease in electrical conductance would result from changes in either distances or contact numbers between conductive fillers. In this work, we prepare microfibers of single walled carbon nanotubes (SWCNTs)/polyvinyl alcohol composites and investigate the electrical conductance and the orientation of SWCNTs upon uniaxial deformation. We also perform extensive Monte Carlo simulations, which reproduce experimental results for the relative decrease in conductance and the SWCNTs orientation. We investigate the electrical networks of SWCNTs in microfibers and find that the decrease in the electrical conductance upon uniaxial deformation should be attributed to a subtle change in the topological structure of the electrical network.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Unraveling the Dynamics of Aminopolymer/Silica Composites

Branched poly(ethylenimine) (PEI) encapsulated within mesoporous silica (SBA-15), has proven to be an eective sorbent for developing carbon capture technologies. However, the structure-property correlations which govern their adsorptive properties is not well understood. By combining coarse-grained molecular dynamics simulations and neutron scattering experiments we are able to construct, and validate, a detailed model of the dynamics and morphology of the conned polymer within the mesoporous support. By varying the simulation properties we are able to probe, for the rst time, the direct relationship between the structure of the polymer and the non-monotonic dynamics of the polymer as a function of monomer concentration within an adsorbing cylindrical pore. Overall the simulation results are in good agreement with quasi-elastic neutron scattering (QENS) studies, suggesting an approach that can be a useful guide for understanding how to tune porous polymer composites for enhancing desired dynamical and structural behavior targeting enhanced carbon dioxide adsorption.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Structure, dynamics and stability of water/scCO 2 /mineral interfaces from ab initio molecular dynamics simulations

Here, the interface between a solid and a complex multi-component liquid forms a unique reaction environment whose structure and composition can significantly deviate from either bulk or liquid phase and is poorly understood due the innate difficulty to obtain molecular level information. Feldspar minerals, as typified by the Ca-end member Anorthite, serve as prototypical model systems to assess the reactivity and ion mobility at solid/water-bearing supercritical fluid (WBSF) interfaces due to recent X-ray based measurements that provide information on water-film formation, and cation vacancies at these surfaces. Using density functional theory based molecular dynamics, which allows the evaluation of reactivity and condensed phase dynamics on equal footing, we report on the structure and dynamics of water nucleation and surface aggregation, carbonation and Ca mobilization under geologic carbon sequestration scenarios (T = 323 K and P = 90 bar). We find that water has a strong enthalpic preference for aggregation on a Ca-rich, O-terminated anorthite (001) surface, but entropy strongly hinders the film formation at very low water concentrations. Carbonation reactions readily occur at electron-rich terminal Oxygen sites adjacent to cation vacancies, when in contact with supercritical CO 2 . Cation vacancies of this type can form readily in the presence of a water layer that allows for facile and enthalpicly favorable Ca 2+ extraction and solvation. Apart from providing unprecedented molecular level detail of a complex three component (mineral, water and scCO 2 ) system), this work highlights the ability of modern capabilities of AIMD methods to begin to qualitatively and quantitatively address structure and reactivity at solid-liquid interfaces of high chemical complexity. This work was supported by the US Department of Energy, Office of Fossil Energy (M.-S. L., B. P. M. and V.-A. G.) and the Office of Basic Energy Science, Division of Chemical Sciences, Geosciences and Biosciences (R.R.), and performed at the Pacific Northwest National Laboratory (PNNL). PNNL is a multi-program national laboratory operated for DOE by Battelle. Computational resources were provided by PNNL’s Platform for Institutional Computing (PIC), the W. R. Wiley Environmental Molecular Science Laboratory (EMSL), a national scientific user facility sponsored by the Department of Energy’s Office of Biological and Environmental Research located at PNNL and the National Energy Research Scientific Computing Center (NERSC) at Lawrence Berkeley National Laboratory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Design, performance, and cost savings of using GF-PC additively manufactured tooling for stamping of HSS 590 sheet metal

Conventional sheet metal forming tooling in the automotive industry is made up of hardened steel and used for mass-production. Prototype tooling made of metal is durable, but it is only used for a small number of parts despite its high cost, contributing heavily to the vehicle development cost. Additive Manufacturing (AM) offers a low-cost alternative for fabricating tooling suitable for low-volume production. Here, this study investigates the feasibility of using AM polymer composite tooling for the stamping of 1.5mm thickness HSS 590 steel sheets through a two-pronged approach – experimental and numerical analysis. Sheet metal stamping experiments were conducted with glass fiber reinforced polycarbonate (GF-PC) AM polymer tooling and their performance was evaluated based on various metrics such as tool deformation and part accuracy. Finite element simulations of the stamping process were performed, which accurately captured the tool deformations seen in experiments with the use of anisotropic material models. The effective use of simulations in optimizing process parameters to achieve the desired final part geometry is also demonstrated. The GF-PC AM polymer composite tooling was found to be well suited for low volume production applications with potential cost savings.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Nanoscale simulation of the thylakoid membrane response to extreme temperatures

Abstract The thylakoid membrane is in a temperature‐sensitive equilibrium that shifts repeatedly during the life cycle in response to ambient temperature or solar irradiance. Plants respond to seasonal temperature variation by changing their thylakoid lipid composition, while a more rapid mechanism for short‐term heat exposure is required. The emission of the small organic molecule isoprene has been postulated as one such possible rapid mechanism. The protective mechanism of isoprene is unknown, but some plants emit isoprene at high temperature. We investigate the dynamics and structure for lipids within a thylakoid membrane across temperatures and varied isoprene content using classical molecular dynamics simulations. The results are compared with experimental findings for temperature‐dependent changes in the lipid composition and shape of thylakoids. The surface area, volume, and flexibility of the membrane, as well as the lipid diffusion, increase with temperature, while the membrane thickness decreases. Saturated thylakoid 34:3 glycolipids derived from eukaryotic synthesis pathways exhibit altered dynamics relative to lipids from prokaryotic synthesis paths, which could explain the upregulation of specific lipid synthesis pathways at different temperatures. Increasing isoprene concentration was not observed to have a significant thermoprotective effect on the thylakoid membranes, and that isoprene readily permeated the membrane models tested.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Evaluation of global simulations of aerosol particle and cloud condensation nuclei number, with implications for cloud droplet formation

A total of 16 global chemistry transport models and general circulation models have participated in this study; 14 model shave been evaluated with regard to their ability to reproduce the near-surface observed number concentration of aerosol particles and cloud condensation nuclei (CCN), as well as derived cloud droplet number concentration (CDNC). Model results for the period 2011–2015 are compared with aerosol measurements(aerosol particle number, CCN and aerosol particle composition in the submicron fraction) from nine surface stations located in Europe and Japan.The evaluation focuses on the ability of models to simulate the average across time state in diverse environments and on the seasonal andshort-term variability in the aerosol properties. There is no single model that systematically performs best across all environments represented by the observations. Models tend to underestimate the observed aerosol particle and CCN number concentrations, with average normalized mean bias (NMB) of all models and for all stations, where dataare available, of –24% and –35% for particles with dry diameters <50 and <120 nm, as well as –36% and –34% for CCNat supersaturations of 0.2% and 1.0%, respectively. Yet, they seem to behave differently for particles activating at very low supersaturations (<0.1%) than at higher ones. A total of 15 models have been used to produce ensemble annual median distributions of relevant parameters. The model diversity (defined as the ratio of standard deviation to mean) is up to about 3 for simulated N 3 (number concentration of particles with dry diameters larger than 3 nm) and up to about 1 for simulated CCN in the extra-polar regions. A global mean reduction of a factor of about 2 is found in the model diversity for CCN at a supersaturation of 0.2% (CCN 0.2 ) compared to that for N 3 , maximizing over regions where new particle formation is important. An additional model has been used to investigate potential causes of model diversity in CCN and bias compared to the observations by performing a perturbed parameter ensemble (PPE) accounting for uncertainties in 26 aerosol-related model input parameters. This PPE suggests that biogenic secondary organic aerosol formation and the hygroscopic properties of the organic material are likely to be the major sources of CCN uncertainty in summer, with dry deposition and cloud processing being dominant in winter. Models capture the relative amplitude of the seasonal variability of the aerosol particle number concentration for all studied particle sizes with available observations (dry diameters larger than 50, 80 and 120 nm). The short-term persistence time (on the order of a few days) of CCN concentrations, which is a measure of aerosol dynamic behavior in the models, is underestimated o naverage by the models by 40% during winter and 20% in summer. In contrast to the large spread in simulated aerosol particle and CCN number concentrations, the CDNC derived from simulated CCN spectra is less diverse and in better agreement with CDNC estimates consistently derived from the observations (average NMB –13% and –22% for updraft velocities 0.3 and 0.6m s –1 , respectively). In addition, simulated CDNC is in slightly better agreement with observationally derived values at lower than at higher updraft velocities (index of agreement 0.64 vs. 0.65). The reduced spread of CDNC compared to that of CCN is attributed to the sublinear response of CDNC to aerosol particle number variations and the negative correlation between the sensitivities of CDNC to aerosol particle number concentration( ∂ N d / ∂ N a ) and to updraft velocity ( ∂ N d / ∂ w ). Overall, we find that while CCN is controlled by both aerosol particle number and composition, CDNC is sensitive to CCN at low and moderate CCN concentrations and to the updraft velocity when CCN levels are high. Discrepancies are found in sensitivities ∂ N d / ∂ N a and ∂ N d / ∂ w ; models may be predisposed to be too“aerosol sensitive” or “aerosol insensitive” in aerosol–cloud–climate interaction studies, even if they may capture average droplet numbers well.This is a subtle but profound finding that only the sensitivities can clearly reveal and may explain inter-model biases on the aerosol indirect effect.

54 ENVIRONMENTAL SCIENCES↗