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At least 73 records · Page 4

Optimal Transport for $e/\pi^0$ Particle Classification in LArTPC Neutrino Experiments

The efficient classification of electromagnetic activity from $\pi^0$ and electrons is a notoriously challenging problem in the reconstruction of neutrino interactions in Liquid Argon Time Projection Chamber (LArTPC) detectors. We address this problem using the mathematical framework of Optimal Transport (OT), which has been successfully employed for event classification in other HEP contexts and is ideally suited to the high-resolution calorimetry of LArTPCs. Using a publicly available simulated dataset from the MicroBooNE collaboration, we show that OT methods achieve state-of-the-art reconstruction performance in $e/\pi^0$ classification. The success of this first application indicates the broader promise of OT methods for LArTPC-based neutrino experiments. This work motivates integrating OT in the reconstruction frameworks of LArTPC experiments such as SBN and DUNE more broadly. Since $\pi^0$s are a significant background for both oscillation experiments and BSM searches, OT can lead to sizeable improvements in the selection efficiency for these analyses by introducing a novel method with which to achieve $\pi^0$ rejection.

Caratelli, David [UC, Santa Barbara]↗

A Model Intercomparison Study of Aerosol‐Cloud‐Turbulence Interactions in a Cloud Chamber: 1. Model Results

This study presents the first model intercomparison of aerosol‐cloud‐turbulence interactions in a controlled cloudy Rayleigh‐Bénard Convection chamber environment, utilizing the Pi Chamber at Michigan Technological University. We analyzed simulated cloud chamber‐averaged statistics of microphysics and thermodynamics in a warm‐phase, cloudy environment under steady‐state conditions at varying aerosol injection rates. Simulation results from seven distinct models (DNS, LES, and a 1D turbulence model) were compared. Our findings demonstrate that while all models qualitatively capture observed trends in droplet number concentration, mean radius, and droplet size distributions at both high and low aerosol injection rates, significant quantitative differences were observed. Notably, droplet number concentrations varied by over two orders of magnitude between models for the same injection rates, indicating sensitivities to the model treatments in droplet activation and removal and wall fluxes. Furthermore, inconsistencies in vertical relative humidity profiles and in achieving steady‐state liquid water content suggest the need for further investigation into the mechanisms driving these variations. Despite these discrepancies, the models generally reproduced consistent power‐law relationships between the microphysical variables. This model intercomparison underscores the importance of controlled cloud chamber experiments for validating and improving cloud microphysical parameterizations. Recommendations for future modeling studies are also highlighted, including constraining wall conditions and processes, investigating droplet/aerosol removal (including sidewall losses), and conducting simplified experiments to isolate specific processes contributing to model divergence and reduce model uncertainties.

54 ENVIRONMENTAL SCIENCES↗

Tuning counterion chemistry to reduce carrier localization in doped semiconducting carbon nanotube networks

Understanding and controlling the impact that electrostatic interactions have on the transport of injected charge carriers is important for the utilization of pi-conjugated semiconductors in opto-electronic applications. Here, we explore the impact of dopant chemical and electronic structure on the doping efficacy and charge carrier transport in semiconducting single-walled carbon nanotube (s-SWCNT) networks using molecular charge-transfer dopants based on functionalized icosahedral dodecaborane (DDB) clusters. Calculations indicate that localization of electron density on the DDB core reduces the coulombic interactions that contribute to hole localization in the s-SWCNTs, thereby improving charge carrier transport. The enhanced delocalization produces an increase in the electrical conductivity and thermopower at lower charge carrier densities, yielding enhanced thermoelectric transport and a thermoelectric power factor that surpasses the previous best in class for enriched s-SWCNT thin-film networks. This strategy can be applied broadly across pi-conjugated semiconductors to tune and enhance performance in a variety of energy harvesting devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Metal-ligand interactions in a redox active ligand system. Electrochemistry and spectroscopy of [M(dipyvd) 2 ] n+ (M=Zn, Ni, n =0, 1, 2)

Reaction of nickel and zinc triflates with the tridentate leucoverdazyl 1-isopropyl-3,5-di (2'-pyridyl)-6-oxo-2H-tetrazine (dipyvdH) and triethylamine resulted in the neutral coordination compounds M(dipyvd) 2 (M = Ni,Zn). In acetonitrile, both compounds undergo two one electron oxidation processes, Zn (dipyvd) 2 at -0.28 V and -0.12 V and Ni(dipyvd) 2 at -0.32 V and -0.15 V vs ferrocene/ferricenium. Oxidations are ligand based resulting in an intermediate mixed valence species and a cationic bis(verdazyl) compound respectively. Oxidation of the ligand changes a localized, antiaromatic, non-planar 8π electron anion to a planar, delocalized 7π electron radical. The change in ligand structure results in an increase in the octahedral ligand field splitting from 10,500 cm –1 to ~13,000 cm –1 , suggesting an increase in the pi acceptor character of the ligand. In the mixed valence species, spectroscopic data suggests minimal interaction between ligands mediated by the metal center; i.e., these are class I-II systems in the Robin-Day classification.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

OsWRKY21 and OsWRKY108 function redundantly to promote phosphate accumulation through maintaining the constitutive expression of OsPHT1;1 under phosphate‐replete conditions

Summary Plant Phosphate Transporter 1 (PHT1) proteins, probably the only influx transporters for phosphate (Pi) uptake, are partially degraded on sufficient Pi levels to prevent excessive Pi accumulation. Therefore, the basal/constitutive expression level of PHT1 genes is vital for maintaining Pi uptake under Pi‐replete conditions. Rice ( Oryza sativa ) OsPHT1;1 is a unique gene as it is highly expressed and not responsive to Pi, however the mechanism for maintaining its basal/constitutive expression remains unknown. Using biochemical and genetic approaches, we identified and functionally characterised the transcription factors maintaining the basal/constitutive expression of OsPHT1;1 . OsWRKY21 and OsWRKY108 interact within the nucleus and both bind to the W‐box in the OsPHT1;1 promoter. Overexpression of OsWRKY21 or OsWRKY108 led to increased Pi accumulation, resulting from elevated expression of OsPHT1;1 . By contrast, oswrky21 oswrky108 double mutants showed decreased Pi accumulation and OsPHT1;1 expression in a Pi‐dependent manner. Moreover, similar to ospht1;1 mutants, plants expressing the OsWRKY21–SRDX fusion protein (a chimeric dominant suppressor) were impaired in Pi accumulation in Pi‐replete roots, accompanied by downregulation of OsPHT1;1 expression. Our findings demonstrated that rice WRKY transcription factors function redundantly to promote Pi uptake by activating OsPHT1;1 expression under Pi‐replete conditions, and represent a novel pathway independent of the central Pi signalling system.

Zhang, Jun↗

Theoretical Studies in Very Strongly Correlated Matter

In this Final Technical Report, a summary of research carried out by the PI and his group from 9/1/2006 to 8/31/2023, on developing new approaches to understand very strongly correlated systems is provided. Novel materials where interactions dominate the kinetic energy (due to hopping motion) of electrons, pose a major puzzle in condensed matter systems. These are located in regimes of parameters where traditional theoretical approaches fail, and new concepts and formalisms are called for. In the area of thermal or thermoelectrical transport the PI has found two new formulas for the Seebeck coefficient. These are easier to apply than the general Kubo formulas, and give interesting insights that lead to new directions in the search for better materials for energy harvesting.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Machine-learning based model reduction for partial differential equations

We develop a novel synergistic approach between model reduction and machine learning. The specific goal of this project is to aid in the construction of reduced order models for basis functions that are custom-made to represent the solution of partial differential equations. Partial differential equations (PDEs) are one of the main mathematical tools for describing physical phenomena. However, due to either efficiency or necessity, for many real-world problems, we are interested in constructing reduced order models (ROMs) which focus only on the explicit computation of subsets of the active spatio-temporal scales in the problem, while treating the interaction with the rest of the scales approximately. The task of accurate representation of such interactions (usually called memory terms) constitutes a vast area of research known as model reduction. PI Stinis has significant expertise in the construction of ROMs for complex systems. In addition, in recent work with the project key participant Qadeer, they have utilized machine learning to acquire custom-made basis functions (CBFs) to expand the solutions of PDEs. In the proposed work, we will merge the two concepts by constructing ROMs for subsets of the CBFs needed to represent the solution of a PDE. Specifically, we will use the Mori-Zwanzig model reduction formalism to construct ROMs for subsets of CBFs for nonlinear PDEs of various complexity, as well as investigate the usage of CBFs in the spectral vanishing viscosity method for problems that can form shocks in finite time. The outcome of the research is aimed to be proof-of-concept about a novel synergistic approach between model reduction and machine learning, thus advancing the field of scientific machine learning. Such a capability will benefit the efficient modeling of physical systems appearing in various areas of interest to the DOE.

97 MATHEMATICS AND COMPUTING↗

The Uranium-Containing and Thorium-Containing Anions Studied by Photoelectron Spectroscopy

An in-depth knowledge of actinide chemistry is fundamental to many aspects of nuclear science and technology, including the synthesis and processing of materials and the remediation of waste disposal sites. Among the actinides, the chemical bonding behaviors of actinium and thorium resemble those of the transition metals; the 5f-electrons of protactinium, uranium, neptunium, and plutonium often play important roles in their bonding; and among the still heavier elements, their bonding tends to mimic the lanthanide elements in terms of electron shielding and their f-electron contributions. Bonding that involves 5f-electrons, however, is especially important, in part because of the significance of uranium and plutonium, but also because these elements are among the few where f-electron participation in bonding is relatively common. This work focused on studying uranium-containing and thorium-containing anions in the gas phase using negative ion photoelectron spectroscopy. Since this technique directly probed valence electrons, it was uniquely positioned to address open questions regarding molecular bonding and electron configurations. A particularly important issue concerned how bonding in actinide-containing molecules was affected by modifications to their actinide atoms’ environment, i.e., due to their interaction with ligands. A closely related question was how actinide atoms’ suborbitals were qualitatively reordered and their energies quantitatively shifted as a result of their ligated environments. These were especially relevant issues in regard to uranium due to it having multiple possible oxidation states (OS) and the potential for 5f electron participation in bonding. The effects of ligands on oxidation states and 5f-orbital energies in uranium bonding was expected to be pronounced. Both ligands and excess electrons were seen as probes of actinide atoms within actinide-containing molecules. Our strategy for advancing knowledge of chemical bonding in the actinide-containing species utilized the synergy between experiments and theory, where in some cases experimental results validated theory and where in others computational results assisted in interpreting experiments. Calculations on actinide systems are terrifically challenging due to large spin-orbit interactions, relativistic effects, and just the sheer number of electrons involved. Even in the simplest species, e.g., U and U2, the most sophisticated, modern calculations carried out by the most experienced theorists often only approximate experimentally-measured values, such as electron affinities. For theory to provide confident predictions that can be used to solve real problems it needed an iterative and ultimately corrective mechanism by which its methods can develop further. Experiments can be used to identify when theory has failed; whereupon the subsequent process of using the experiment-theory interplay can be used to find the cause of the failure. Upon fixing it in one case, different test species can be proposed and studied by the experiment-theory combination to determine whether the problem has been corrected. Thus, experiments not only measure the values of molecular properties, they also provide navigational 3 beacons that keep computations off the reefs in an otherwise dark sea with few reference points. Experimental measurements in the actinide field are not only important, they are in actuality essential to computational progress. While it was not always possible to compare the theoreticallydetermined quantity of interest directly with the same experimentally-measured observable, it was usually possible to compare consequential properties that are both calculable and measurable. In the work completed here electron affinities and electronic state spacings were often sensitive consequential parameters. Reasonable agreement between measured and computational values signaled that a calculation that was very likely to be on-track. We had established collaborative relationships with five computational groups, all of which have expertise in computational actinide chemistry. Their PI’s are L. Cheng, D. Dixon, L. Gagliardi, K. Peterson, and B. Vlaisavljevich. Our close interaction with our theory partners led to us suggesting systems to them and them to us. This reciprocal interaction between our experimental and their computational results was among the most important strengths of this work and was a thread woven throughout. Even though anion photoelectron spectroscopic studies are conducted on anions, much of the information that they provide, pertains to the electronic structure of the neutral counterparts of those anions; among these are electron affinities and electronically excited state spacings. Our experimental tools included several specialized ion sources for forming the anionic species of interest, a mass spectrometer for identifying and mass-selecting them, and an anion photoelectron spectrometer for determining their electron affinities (EA) and characterizing the electronic states of the selected anions’ neutral counterparts. Anion photoelectron spectroscopy is conducted by crossing a mass-selected beam of anions with a fixed-frequency laser beam and energy-analyzing the resultant photodetached electrons. The photodetachment process is governed by the energyconserving relationship: hν = EBE + EKE, where hν is the photon’s energy, EBE is the electron binding (photodetachment transition) energy, and EKE is the electron’s kinetic energy. In our apparatus mass-selection is accomplished via time-of-flight mass spectrometry (TOF-MS), electron energy analysis is achieved with either a magnetic bottle or by velocity mapped imaging. Photodetachment of electrons from anions is implemented via either Nd:YAG or excimer lasers. The photodetachment transition energy, i.e., the EBE, between the ground vibrational and electronic state of an anion and the ground vibrational and electronic state of that anion’s neutral counterpart is the adiabatic electron affinity (EA) of that neutral molecule. Likewise, photodetachment transitions between the ground vibrational and electronic state of an anion and the various electronically-excited states of that anion’s corresponding neutral map the electronic spectrum of that neutral species, i.e., the spectral spacings in the photoelectron spectrum are a mirror image of the neutral’s electronic spectrum. It was, of course, crucial to be able to form the anionic species of interest. There, we had a particularly broad field of anion sources from which to choose. These included several variants of pulsed laser vaporization (LV), laser photoemission, infrared desorption plus photoemission, pulsed arc discharge (PACIS), electrospray ionization (ESI), and Rydberg electron transfer (RET). Each of these anion sources were readily combined with, i.e., connected to, the anion photoelectron spectroscopic portion of our apparatus as described above. Among the sources that utilize lasers, visible light for LV sources as well as IR for desorption sources are provided by Nd:YAG lasers. Ultraviolet photons are provided by both Nd:YAG and excimer lasers, whereas the excitation wavelengths for RET experiments come from two Nd:YAG-pumped dye lasers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Measurements of $\pi ^\pm $, $K^\pm $, p and $\bar{p}$ spectra in $^{40}\hbox {Ar+}^{45}\hbox {Sc}$ collisions at 13A to 150A $\text{ Ge }\hspace{-1.00006pt}\text{ V }\!/\!c$

The NA61/SHINE experiment at the CERN Super Proton Synchrotron studies the onset of deconfinement in strongly interacting matter through a beam energy scan of particle production in collisions of nuclei of varied sizes. This paper presents results on inclusive double-differential spectra, transverse momentum and rapidity distributions and mean multiplicities of $\pi ^\pm $, $K^\pm $, p and $\bar{p}$ produced in $^{40}\hbox {Ar+}^{45}\hbox {Sc}$ collisions at beam momenta of 13A, 19A, 30A, 40A, 75A and 150A $\text{ Ge }\hspace{-1.00006pt}\text{ V }\!/\!c$. The analysis uses the 10% most central collisions, where the observed forward energy defines centrality. The energy dependence of the $K^\pm $/$\pi ^\pm $ ratios as well as of inverse slope parameters of the $K^\pm $ transverse mass distributions are placed in between those found in inelastic $p+p$ and central Pb + Pb collisions. The results obtained here establish a system-size dependence of hadron production properties that so far cannot be explained either within statistical or dynamical models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

$K^{*}(892)^0$ meson production in inelastic p+p interactions at 40 and 80 $\text{ GeV }\!/\!c$ beam momenta measured by NA61/SHINE at the CERN SPS

Measurements of $K^{*}(892)^0$ resonance production via its $K^{+}\pi ^{-}$ decay mode in inelastic p+p collisions at beam momenta 40 and 80 $\text{ GeV }\!/\!c$ ($\sqrt{s_{NN}}=8.8$ and 12.3 $\text{ GeV }$) are presented. The data were recorded by the NA61/SHINE hadron spectrometer at the CERN Super Proton Synchrotron. The template method was used to extract the $K^{*}(892)^0$ signal. Transverse momentum and rapidity spectra were obtained. The mean multiplicities of $K^{*}(892)^0$ mesons were found to be $(35.1 \pm 1.3 \mathrm {(stat)} \pm 3.6 \mathrm {(sys))} \cdot 10^{-3}$ at 40 $\text{ GeV }\!/\!c$ and $(58.3 \pm 1.9 \mathrm {(stat)} \pm 4.9 \mathrm {(sys))} \cdot 10^{-3}$ at 80 $\text{ GeV }\!/\!c$. The NA61/SHINE results are compared with the Epos1.99 and Hadron Resonance Gas models as well as with world data. The transverse mass spectra of $K^{*}(892)^0$ mesons and other particles previously reported by NA61/SHINE were fitted within the Blast-Wave model. The transverse flow velocities are close to 0.1–0.2 of the speed of light and are significantly smaller than the ones determined in heavy nucleus-nucleus interactions at the same beam momenta.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Anisotropic Coarse-Grained Model for Conjugated Polymers: Investigations into Solution Morphologies

The optoelectronic properties of conjugated polymers are dictated by the interplay of multiscale structural features, including intrachain dihedrals, interchain pi-pi stacking, and the complex mesoscale morphology. While much is known about the structures of polymers with isotropically interacting monomers, little is known about polymers with strongly anisotropic backbone monomers, a class of materials to which conjugated polymers belong. Fundamental understanding is further complicated when the semiflexible and molecularly heterogeneous nature of conjugated polymers is taken into account. We present an anisotropic coarse-grained (CG) model for conjugated polymers that incorporates key molecular features (monomer anisotropy, intermonomer dihedrals, and side chains). Finally, the model is employed to characterize the single-chain conformational properties of conjugated polymers, revealing a rich temperature-dependent conformational landscape. These studies provide a critical link between CG molecular descriptors and conformational ordering in conjugated polymers.

36 MATERIALS SCIENCE↗

Amplitude Analysis of $\omega\pi^0$ Photoproduction at GlueX

Excited meson states can often lie hidden within mass spectra beneath more dominant resonances, making it difficult to extract their physical properties. We can unveil these states through amplitude analysis, which disentangles the overlapping states via fits to their unique production and decay angular distributions. Understanding the light-meson spectrum is essential for confirming Lattice QCD predictions, especially in regards to the search for possible hybrid mesons. The Gluonic Excitation (GlueX) experiment at Jefferson Lab aids this search by studying the production of excited light mesons in $\gamma p$ interactions in the 8.2 - 8.8 GeV photon-beam energy range. We show in these proceedings preliminary results of an amplitude analysis of a large $\omega\pi^0$ dataset, concentrating on measuring the interference between the $b_1(1235)$ and an excited $J^{PC}=1^{--}$ vector resonance.

Scheuer, Kevin↗

Seismic Waveform Inversion Capability on Resource-Constrained Edge Devices

Seismic full wave inversion (FWI) is a widely used non-linear seismic imaging method used to reconstruct subsurface velocity images, however it is time consuming, has high computational cost and depend heavily on human interaction. Recently, deep learning has accelerated it’s use in several data-driven techniques, however most deep learning techniques suffer from overfitting and stability issues. In this work, we propose an edge computing-based data-driven inversion technique based on supervised deep convolutional neural network to accurately reconstruct the subsurface velocities. Deep learning based data-driven technique depends mostly on bulk data training. In this work, we train our deep convolutional neural network (DCN) (UNet and InversionNet) on the raw seismic data and their corresponding velocity models during the training phase to learn the non-linear mapping between the seismic data and velocity models. The trained network is then used to estimate the velocity models from new input seismic data during the prediction phase. The prediction phase is performed on a resource-constrained edge device such as Raspberry Pi. Raspberry Pi provides real-time and on-device computational power to execute the inference process. In addition, we demonstrate robustness of our models to perform inversion in the presence on noise by performing both noise-aware and no-noise training and feeding the resulting trained models with noise at different signal-to-noise (SNR) ratio values. We make great efforts to achieve very feasible inference times on the Raspberry Pi for both models. Specifically, the inference times per prediction for UNet and InversionNet models on Raspberry Pi were 22 and 4 s respectively whilst inference times for both models on the GPU were 2 and 18 s which are very comparable. Finally, we have designed a user-friendly interactive graphical user interface (GUI) to automate the model execution and inversion process on the Raspberry Pi.

Manu, Daniel (ORCID:0000000154982677)↗

NCSU Flux Tower Data

NCSU Flux Tower Data Level b1: QC checks applied to measurements Data Format: CSV Description: See "instrument descripotion Site: Houston, TX; Tracking Aerosol Convection interactions ExpeRiment (HOU) Location: Houston, TX; AMF1 (main site for TRACER) Facility Code: M1 Category: Aerosol Properties Data Type: PI Data Source Instrument/Data: Sonic Anemometer, 3 Condensation Particle Counters, 1 SP2, 1 POPS Start Date: 2022-06-01 End Date: 2022-9-26 Contact PI: Markus Petters (mdpetter@ncsu.edu) Funding Source: DOE ASR award US Department of Energy, Office of Science, Biological and Environment Research (grant no. DE-SC 0021074) Instrument description The NCSU flux tower was located next to the AMF sampling pad. The flux tower consisted of a 10 m telescoping tower. Mounted at the top of the tower was a sonic anemometer (RM Young 8000) and a Krypton Hygrometer. A sample line (¼” conductive tubing) and communication line was laid to a trailer located underneath and slightly adjacent to the tower. The sample line brought aerosol inside the trailer at 4.5 L min-1, where it was distributed between 3 CPCs (TSI 3776c, Dc ~ 2.5 nm, TSI 3771, Dc ~10nm, and TSI 3772, Dc ~40 nm) with different size cuts. Also sampling was a printed particle optical spectrometer (POPS) and a single particle soot photometer (SP2). Please contact mdpetter@ncsu.edu for further information.

54 ENVIRONMENTAL SCIENCES↗

NCSU RDMA data

NCSU RDMA Data Level b1: QC checks applied to measurements Data Format: CSV Description: See "instrument description Site: Houston, TX; Tracking Aerosol Convection interactions ExpeRiment (HOU) Location: Houston, TX; AMF1 (main site for TRACER) Facility Code: M1 Category: Aerosol Properties Data Type: PI Data Source Instrument/Data: Nano-Scanning Mobility Particle (SMPS); A Radial Differential Mobility Analyzer (RDMA) coupled with 1 Condensation Particle Counter Start Date: 2022-06-01 End Date: 2022-9-26 Contact PI: Markus Petters (mdpetter@ncsu.edu) Funding Source: DOE ASR award US Department of Energy, Office of Science, Biological and Environment Research (grant no. DE-SC 0021074) Instrument description The NCSU RDMA was operated at a sheath-to-sample flow ratio of 5:1.5 L min−1. The RDMA was configured to scan from 5 to 55 nm. It was located into the temperature-controlled trailer adjacent to the NCSU Flux Tower to observe size distributions of the aerosols.The sample line was dried with three silica-gel driers in series, and then neutralized with X-ray neutralizer. Please contact mdpetter@ncsu.edu for further information.

54 ENVIRONMENTAL SCIENCES↗

NCSU HTDMA data

NCSU HTDMA data Data Level b1: QC checks applied to measurements Data Format: CSV Description: See "instrument description Site: Houston, TX; Tracking Aerosol Convection interactions ExpeRiment (HOU) Location: Houston, TX; AMF1 (main site for TRACER) Facility Code: M1 Category: Aerosol Properties Data Type: PI Data Source Instrument/Data: Humidified Tandem Differential Mobility Analyzer; 2 Differential Mobility Analyzers (DMA1 and DMA2). Start Date: 2022-06-01 End Date: 2022-09-26 Contact PI: Markus Petters (mdpetter@ncsu.edu) Funding Source: DOE ASR award US Department of Energy, Office of Science, Biological and Environment Research (grant no. DE-SC 0021074) Instrument description The NCSU HTDMA was operated at a sheath-to-sample flow ratio of 5:1 L min−1. The HTDMA was configured to measure hygroscopic growth factors of dry particles with mobility diameters of D = 15, 20, 30, 40, and 50 nm at RH ~ 70%. A complete cycle for all diameters took ~30 minutes. A sample line brought aerosol inside the trailer at 2.5 L min-1, where it was distributed between NCSU RDMA (1.5 L min-1) and NCSU HTDMA (1 L min-1) lines. The sample line was dried with three silica-gel driers in series, and then neutralized with X-ray neutralizer. The sample line entered DMA1 (operated as an electrostatic classifier). Monodisperse particles with certain fractions were humidified with temperature controlled Nafion membrane immersed in water before entering DMA2 (operated in scanning mobility particle sizer). Please contact mdpetter@ncsu.edu for further information.

54 ENVIRONMENTAL SCIENCES↗