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At least 703 records · Page 39

Computational study of the electrostatic potential and charges of multivalent ionic liquid molecules

The electrostatic interactions in ionic liquids (ILs) can be difficult to quantify, but this information is very valuable for improving intermolecular potentials for performing molecular-level simulations. Although polarizable forcefields can provide improved accuracy, the computational efficiency of fixed charge molecular models is often preferred for larger systems. Here, we propose a multi-scale screening approach for analyzing the charge scaling behavior and other electrostatic properties of ILs, which is more attainable than previous analysis methods that rely on the IL crystalline structures. Based on isolated molecules and small clusters, we study the electrostatic potential properties and charges of multivalent IL molecules using density-functional theory calculations and ab initio molecular dynamics simulations. The charges of the IL molecules are calculated and compared using several different charge estimation techniques. Although there are some differences among the estimated partial charges on the atoms, the total anion and cation charges are very similar. In conclusion, the charge scaling factors are substantial, and they are only slightly affected by the IL cluster size model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Carbon-carbon interactions in warm dense titanium carbide

Encouraged by experimental reports of diamond precipitation in carbon-containing materials under warm dense matter conditions and in shock compression experiments, we examine the behavior of carbon in TiC using density functional theory-molecular dynamics simulations. Two polymorphs of TiC are considered, the ambient-pressure B1 ($Fm$$\overline{3}$$m$) structure in which C-C interactions are prevented by geometric constraints, and a high-pressure Cmcm structure in which C atoms condense into zigzag chains. Chemistry-inspired bonding analyses confirm the covalently bound nature of these chains and further illuminate important interatomic interactions in both structures. Upon melting of B1 TiC, new short-range C-C interactions develop in the liquid, while the pre-existing C-C interactions in Cmcm TiC persist in the liquid. Here, the resulting carbon networks in the melt provide a promising environment for eventual diamond nucleation.

Ab initio molecular dynamics↗

Multiple Environmental Influences on the Lightning of Cold-Based Continental Cumulonimbus Clouds. Part I: Description and Validation of Model

In this two-part paper, influences from environmental factors on lightning in a convective storm are assessed with a model. In Part I, an electrical component is described and applied in the Aerosol–Cloud model (AC). AC treats many types of secondary (e.g., breakup in ice–ice collisions, raindrop-freezing fragmentation, rime splintering) and primary (heterogeneous, homogeneous freezing) ice initiation. AC represents lightning flashes with a statistical treatment of branching from a fractal law constrained by video imagery. The storm simulated is from the Severe Thunderstorm Electrification and Precipitation Study (STEPS; 19/20 June 2000). The simulation was validated microphysically [e.g., ice/droplet concentrations and mean sizes, liquid water content (LWC), reflectivity, surface precipitation] and dynamically (e.g., ascent) in our 2017 paper. Predicted ice concentrations (~10 L -1 ) agreed—to within a factor of about 2—with aircraft data at flight levels (-10° to -15°C). Here, electrical statistics of the same simulation are compared with observations. Flash rates (to within a factor of 2), triggering altitudes and polarity of flashes, and electric fields, all agree with the coincident STEPS observations. The “normal” tripole of charge structure observed during an electrical balloon sounding is reproduced by AC. It is related to reversal of polarity of noninductive charging in ice–ice collisions seen in laboratory experiments when temperature or LWC are varied. Positively charged graupel and negatively charged snow at most midlevels, charged away from the fastest updrafts, is predicted to cause the normal tripole. Total charge separated in the simulated storm is dominated by collisions involving secondary ice from fragmentation in graupel–snow collisions.

54 ENVIRONMENTAL SCIENCES↗

Atomic Cluster Aggregates in Nucleation of Solid Alumina Inclusion in the Aluminum Deoxidation for Liquid Iron

Nucleation plays a decisive role in determining the structure and size distribution of a solid inclusion particle in liquid iron. The literature does not yet provide a clear picture about the pathway leading to solid alumina inclusion from liquid iron. The main confusion surrounds the little-known structures and thermodynamic properties of metastable alumina phase (MAP) that appear in the nucleation of alumina inclusion. In this work, it is suggested that MAP could appear in the Al-deoxidation reaction, based on the summaries and analysis in terms of various equilibrium experimental results and thermodynamic modeling of the Al deoxidation in liquid iron since the 1950s. The structures and thermodynamic properties of a species of MAP, alumina atomic cluster aggregates (AACAs), are calculated by density functional theory (DFT) methods. The thermodynamics on formation and transformation of AACAs shows that AACAs are in equilibrium with Al and O with various contents measured in the Al-deoxidation equilibrium experiments for liquid iron. It is suggested that the residual Al and O, which cannot nucleate, appear in the form of AACAs in Al-deoxidized liquid iron. It can be concluded that AACAs are the metastable intermediates and structural units for alumina inclusion nucleating from liquid iron. Thus, the behaviors of AACAs are important to the control of the nucleation rate of alumina inclusions in the Al deoxidation for liquid iron.

36 MATERIALS SCIENCE↗

How initial conditions-, structural-, and parameter-based model uncertainty interact and influence predictions in permafrost ecosystems: Modeling Archive

This dataset contains model output and input data, as well as source code examples for the Terrestrial Ecosystem Model with the Dynamic Vegetation Model and Dynamic Organic Soil (DVM-DOS-TEM) for the field sites Imnavait creek and the Bonanza creek Long Term Ecological Research Network (LTER). The data covers simulations from the last glacial maximum (LGM) until 2100 for a selection of paleo scenarios, setting the mean temperature of the LGM up to 10°C lower than pre-industrial conditions. The model structure was modulated to represent various model versions, and this dataset contains the relevant changes in the source code. The raw output data, the processed statistical data, the setup and processing scripts as well as parameter value distribution files from a parameter sensitivity analysis are included as well. Model outputs include active layer depth, organic soil carbon, soil layer depths, gross primary productivity (GPP) with and without nitrogen limitation, net primary productivity (NPP), soil liquid water content, heterotrophic, maintenance, and growth respiration, soil temperature, and vegetation carbon (*.nc files). The Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) project is a research effort to reduce uncertainty in the Department of Energy’s Energy Exascale Earth System Model (E3SM) by developing a predictive understanding of Arctic tundra ecosystems underlain by permafrost and to quantify feedbacks from the Arctic tundra to the Earth system. NGEE Arctic is supported by the Department of Energy's Office of Biological and Environmental Research.Over Phases 1–3, observations made by the NGEE Arctic team across a gradient of permafrost landscapes in Arctic Alaska improved the representation of tundra processes in the land surface component of E3SM (the E3SM Land Model, ELM). Model improvements emphasized unique aspects of permafrost environments and explored reductions in model complexity while retaining predictive power. The Arctic-informed ELM developed by NGEE Arctic has been used to make novel predictions on processes ranging from permafrost thaw to soil biogeochemical cycling to Earth system feedbacks associated with the unique characteristics of tundra plants. In Phase 4, the NGEE Arctic team is evaluating our new predictive understanding under novel conditions across the Arctic domain. In collaboration with partners at long-term pan-Arctic research sites we are examining whether an Arctic-informed ELM can faithfully simulate interactions among surface and subsurface processes at site, regional, and pan-Arctic scales. In turn, we are using variety of tools to dynamically extend and evaluate ELM inference, with an emphasis on data synthesis and pan-Arctic model evaluation, reintegration of code with an evolving E3SM, scaling across heterogeneous Arctic landscapes, and the appropriate representation of the impacts of increasingly frequent Arctic disturbances.

54 ENVIRONMENTAL SCIENCES↗

Melatonin-Induced Modulation of Cholesterol-Enriched Model Neuronal Membranes

Melatonin, a hormone primarily produced by the brain’s pineal gland, not only regulates circadian rhythms, but also influences the structural and biophysical properties of neuronal membranes. Its amphiphilic nature enables direct incorporation into lipid bilayers and preferential interactions with cholesterol-rich lipid rafts, critical hubs for cellular signaling and membrane organization. Despite increasing recognition of its membrane activity, the molecular basis of melatonin’s interactions with coexisting liquid-ordered (L o ) and liquid-disordered (L d ) phases remains unclear. Here, in this study, we combine small-angle neutron scattering (SANS) and all-atom molecular dynamics simulations to examine model neuronal membranes composed of DSPC, DOPC, POPC, and cholesterol. Our results show that melatonin preserves domain morphology while adopting distinct orientations within the bilayer and at the membrane interface, allowing both lateral and transmembrane bridging across lipid phases. These findings establish the molecular underpinnings of melatonin’s modulation of membrane heterogeneity and provide strong support for its receptor-independent actions.

atomistic simulations↗

Renormalized site density functional theory for models of ion hydration

Development of accurate statistical mechanics models of molecular liquid systems is a problem of great practical and fundamental importance. Site-density functional theory (SDFT) is one of the promising directions in this area, but its success hinges upon the ability to efficiently reconcile co-existence of two distinct intra- and inter-molecular interaction regimes in a molecular liquid. Renormalized formulation of site-density functional theory (RSDFT), that we have recently developed, resolves this problem by introducing an additional potential field variable that decouples two interaction scales and maps the molecular liquid problem onto the effective simple liquid mixture. This work provides a critical assessment of RSDFT for the hydrated ion system - a problem, which historically has always been one of the most difficult cases for SDFT applications. Using two-site model of water, we perform a comprehensive analysis of hydrated alkali metal and halogen ions, including both structural and free energy based characteristics. The results indicate that RSDFT provides a significant improvement over conventional 3D-RISM implementations, and may prove useful in coarse grained simulations based on two-site solvent models.

Chuev, Gennady N.↗

Universal and interpretable classification of atomistic structural transitions via unsupervised graph learning

Materials processing often occurs under extreme dynamic conditions leading to a multitude of unique structural environments. These structural environments generally occur at high temperatures and/or high pressures, often under non-equilibrium conditions, which results in drastic changes in the material's structure over time. Computational techniques, such as molecular dynamics simulations, can probe the atomic regime under these extreme conditions. However, characterizing the resulting diverse atomistic structures as a material undergoes extreme changes in its structure has proved challenging due to the inherently non-linear relationship between structures as large-scale changes occur. Here, we introduce SODAS++, a universal graph neural network framework, that can accurately and intuitively quantify the atomistic structural evolution corresponding to the transition between any two arbitrary phases. We showcase SODAS++ for both solid–solid and solid–liquid transitions for systems of increasing geometric and chemical complexity, such as colloidal systems, elemental Al, rutile and amorphous TiO 2 , and the non-stoichiometric ternary alloy Ag 26 Au 5 Cu 19 . Finally, we show that SODAS++ can accurately quantify all transitions in a physically interpretable manner, showcasing the power of unsupervised graph neural network encodings for capturing the complex and non-linear pathway, a material's structure takes as it evolves.

36 MATERIALS SCIENCE↗

Adiabatic and radiative cooling are both important causes of aerosol activation in simulated fog events in Europe

Aerosol–fog interactions affect the visibility in, and life cycle of, fog and are difficult to represent in weather and climate models. Here we explore processes that impact the simulation of fog droplet number concentrations (N d ) at sub-kilometer scale horizontal grid resolutions in the UK Met Office Unified Model. We modify the parameterization of aerosol activation to include droplet activation by radiative cooling in addition to adiabatic cooling and determine the relative importance of the two cooling mechanisms. We further test the sensitivity of simulated N d to: (a) interception of droplets by trees and buildings, (b) overestimation of updrafts in temperature inversions (which leads to artificially high N d values), and (c) potential mechanisms for droplet deactivation due to downward fluctuations in supersaturation. We evaluate our model against observations from the ParisFog and LANFEX field campaigns, building on evaluation described in the companion paper. Including radiative cooling in the activation mechanism improves how accurately we represent the liquid water path and the vertical structure of the fog in our LANFEX case study. However, with radiative cooling, the N d are overestimated for most of the ParisFog cases and for the LANFEX case. The time-averaged overestimate exceeds a factor of three (the normalized mean bias factor exceeds 2.0) in 4 out of 11 ParisFog cases. Our sensitivity studies demonstrate how these overestimates can be mitigated. Assuming the overestimate affects both radiative and adiabatic cooling, we find that although radiative cooling is more often the dominant source, both cooling sources can sometimes dominate activation.

Ghosh, Pratapaditya [Carnegie Mellon University, P↗

Assessment of the cloud liquid water from climate models and reanalysis using satellite observations

We perform here a model-observation comparison and report on the state-of-the-art cloud liquid water content (CLWC) and path (CLWP) outputs from the present-day global climate models (GCMs) simulations in CMIP3/CMIP5, two other GCMs (UCLA and GEOS5) and two reanalyses (ECMWF Interim and MERRA) in comparison with two satellites observational datasets (CloudSat and MODIS). We use two different liquid water observation products from CloudSat and MODIS, for CLWP and their combined product for LWC with a method to remove the contribution from precipitating and convective core hydrometeors so that more meaningful model-observation comparisons can be made. Considering the CloudSat’s limitations of CLWC retrievals due to contamination from the precipitation and from radar clutter near the surface, an estimate CLWC is synergistically constructed using MODIS CLWP and CloudSat CLWC. The model-observation comparison shows that most of the CMIP3/CMIP5 annual mean CLWP values are overestimated by factors of 2 - 10 compared to observations globally. There are a number of CMIP5 models, including CSIRO, MPI, and the UCLA GCM that perform well compared to the other models. For the vertical structure of CLWC, significant systematic biases are found with many models biased significantly high above the mid-troposphere. In the tropics, systematic high biases occur at all levels above 700 hPa. Based on the Taylor diagram, the ensemble performance of CMIP5 CLWP simulation shows little or no improvement relative to CMIP3.

54 ENVIRONMENTAL SCIENCES↗

Water mediated growth of oriented single crystalline SrCO3 nanorod arrays on strontium compounds

Abstract Morphology-controlled strontianite nanostructures have attracted interest in various fields, such as electrocatalyst and photocatalysts. Basic additives in aqueous strontium solutions is commonly used in controlling strontianite nanostructures. Here, we show that trace water also serves an important role in forming and structuring vertically oriented strontianite nanorod arrays on strontium compounds. Using in situ Raman spectroscopy, we monitored the structural evolution from hydrated strontium to strontianite nanorods, demonstrating the epitaxial growth by vapor–liquid–solid mechanism. Water molecules cause not only the exsolution of Sr liquid droplets on the surface but also the uptake of airborne CO 2 followed by its ionization to CO 3 2− . The existence of intermediate SrHO + –OCO 2 2− phase indicates the interaction of CO 3 2− with SrOH + in Sr(OH) x (H 2 O) y cluster to orient strontianite crystals. X-ray diffraction simulation and transmission electron microscopy identify the preferred-orientation plane of the 1D nanostructures as the (002) plane, i.e., the growth along the c-axis. The anisotropic growth habit is found to be affected by the kinetics of carbonation. This study paves the way for designing and developing 1D architecture of alkaline earth metal carbonates by a simple method without external additives at room temperature.

36 MATERIALS SCIENCE↗

Adaptive spherical lens

This paper reports the creation of a tandem liquid crystal cell arrangement capable of simulating the performance of a spherical lens. Electrical modulation of the index of refraction creates focusing behavior. The modulation is induced by a set of electrodes whose individual voltages are arranged to provide a cylindrical exit wave front for a uniform plane-wave input. Two such cells with orthogonal electrodes arranged in cascade create spherical lens performance. Experimental evidence using a lens with a relatively small number of electrodes is presented. Applications for such structures, once improved, would include real-time focus adjustment for optical disk readers and hand-held photographic equipment as well as aberration compensation for long path-length optical systems.

Kowel, S. T.↗

On the determination of the origin of linear anomaly in the macrostructure of VPPA welded 2219-T87 aluminum alloy: Preliminary report

The cause and significance of the weld radiograph enigma, which is a linear anomaly in the features of the X-ray film is examined. By observing features on available radiographs and in studying published reports of similar features, it was possible to conclude that there are many manifestations of the enigma, and that they are all specific features of fine structure in radiographs due to natural processes connected with welding and to specific X-ray absorption and diffraction phenomena. These processes include the thermal distribution and liquid metal flow in welding, the development of microstructure, morphology, second phase particles and porosity due to the solidification process, and to the pattern of residual stresses after the weld metal has cooled to the ambient temperature. Microdensitometer traces were made across weld radiographs of standard enigmatic types. Similar patterns were produced by computer simulation. These show that the enigma is a relatively low contrast feature compared to real weld defects, such as undercuts or centerline cracks. The enigma can be distinguished from weld defects by these microdensitometer traces. The enigma effect on weld properties is not known but is expected to be minor.

Jemian, W. A.↗

Alabama NASA EPSCoR Preparation Grant Program: Grant No. NCC5-391

The funded research projects under the Experimental Program to Stimulate Cooperative Research (EPSCoR) grant program and the student fellowship awards are summarized in this report. The projects include: 1) Crystallization of Dehydratase/DcoH: A Target in Lung Disease; 2) Measuring Velocity Profiles in Liquid Metals using an Ultrasonic Doppler Velocimeter; 3) Synthesis, Structure, and Properties of New Thermoelectric Materials; 4) Computational Determination of Structures and Reactivity of Phenol-Formaldehyde Resins; 5) Synthesis of Microbial Polyesters in the NASA Bioreactor; 6) Visualization of Flow-Fields in Magnetocombustion; 7) Synthesis of Fluorescent Saccharide Derivatives. The student fellowship awards include: 1) Distributed Fusion of Satellite Images; 2) Study of the Relationship between Urban Development, Local Climate, and Water Quality for the Atlanta, Georgia Metrop; 3) Computer Simulation of the Effectiveness of a Spring-Loaded Exercise Device.

Gregory, John C.↗

Computational Non-Destructive Evaluation Improving Ultrasonic Interrogation of Complex Geometry Composite Parts

Finite element simulation was employed in modeling the ultrasound (UT) pressure pulse propagation through a coupled liquid-composite medium to reproduce experimental data. From the simulation point of view, the proposed approach is challenging when there is a large simulation domain. For example, it is shown that a sub-micron wavelength of an ultrasonic wave requires a mesh size of several microns and this in turn requires significant computational resources, as well as special care in modeling. Some of the simulation results are presented considering that such modeling should reproduce experimental data for a healthy and faulty composite structure with complex geometry. Many possible experimental setups are simulated to demonstrate the non-destructive testing technique. This setup includes the generation of pressure pulse propagating through the tested composite plate and possible scattering by discontinuities (area of different impedance) that may be present in the panel. This scattered pulse together with the baseline pressure pulse generates a signature on the probe element which can be used to locate the position of defects in the structures.

modeling↗

Neutrino beam bunch structure reconstruction with precision timing in the ICARUS liquid argon time projection chamber

The ICARUS detector has been operating smoothly since 2021 as the far detector in the Short Baseline Neutrino (SBN) program at Fermilab, collecting neutrino interactions from both the Booster Neutrino Beam (BNB) and off-axis from the Neutrinos at the Main Injector (NuMI) beam. Analysis of neutrino interactions in ICARUS requires mitigation of substantial cosmogenic backgrounds. This is achieved by using an external Cosmic Ray Tagger (CRT) and a Photomultiplier Tube (PMT) system embedded in the liquid argon. The intrinsic neutrino beam bunch structure, inherited time structure from the Radio Frequency (RF) system used to accelerate the protons, can be resolved at the ICARUS detector using precise timing information. Located at shallow depth, ICARUS is exposed to a high flux of cosmic rays that can be mistaken for neutrino interactions. To mitigate this background, the CRT and a 3-meter-thick concrete overburden were installed. To better model backgrounds, ICARUS makes use of an overlay technique where simulated neutrino events are superimposed on detector beam-off data. PMTs installed within a Time Projection Chamber detect argon scintillation light emitted by high energy charged particles passing through the chamber and provide the event timing of neutrino interactions. The nanosecond-level beam bunch structure is reconstructed with the PMT system and can be used to further understand backgrounds and enhance neutrino physics capabilities. In this thesis, I will discuss background mitigation techniques using precision timing and present a novel technique to select neutrino events from our unbiased data stream using the beam bunch structure.

Heggestuen, Anna [Colorado State U.] (ORCID:000000↗