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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Development of compact tokamak fusion reactor use cases to inform future transport studies

The OMFIT STEP (Meneghini et al. , Nucl. Fusion , vol. 10, 2020, p. 1088) workflow has been used to develop inductive and steady-state H-mode core plasma scenario use cases for a $B_0 = 8 \, {\rm T}$ , $R_0 = 4 \, {\rm m}$ machine to help guide and inform future higher-fidelity studies of core transport and confinement in compact tokamak reactors. Both use cases are designed to produce 200 MW or more of net electric power in an up-down symmetric plasma with minor radius $a = 1.4 \, {\rm m}$ , elongation $\kappa = 2.0$ , triangularity $\delta = 0.5$ and effective charge $Z_{{\rm eff}} \simeq 2$ . Additional considerations based on the need for compatibility of the core with reactor-relevant power exhaust solutions and external actuators were used to guide and constrain the use case development. An extensive characterization of core transport in both scenarios is presented, the most important feature of which is the extreme sensitivity of the results to the quantitative stiffness level of the transport model used as well as the predicted critical gradients. This sensitivity is shown to arise from different levels of transport stiffness exhibited by the models, combined with the gyroBohm-normalized fluxes of the predictions being an order of magnitude larger than other H-mode plasmas. Additionally, it is shown that although heating in both plasmas is predominantly to the electrons and collisionality is low, the plasmas remain sufficiently well coupled for the ions to carry a significant fraction of the thermal transport. As neoclassical transport is negligible in these conditions, this situation inherently requires long-wavelength ion gyroradius-scale turbulence to be the dominant transport mechanism in both plasmas. These results are combined with other basic considerations to propose a simple heuristic model of transport in reactor-relevant plasmas, along with simple metrics to quantify coupling and core transport properties across burning and non-burning plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Protection against Chemical Warfare Agents and Biological Threats Using Metal–Organic Frameworks as Active Layers

The SARS-CoV-2 pandemic outbreak and the unfortunate misuse of toxic chemical warfare agents (CWAs) highlight the importance of developing functional materials to protect against these chemical and pathogen threats. Metal–organic frameworks (MOFs), which comprise a tunable class of crystalline porous materials built from inorganic nodes and organic linkers, have emerged as a class of heterogeneous catalysts capable of rapid detoxification of multiple classes of these harmful chemical or biological hazards. In particular, zirconium-based MOFs (Zr-MOFs) feature Lewis acidic nodes that serve as active sites for a wide range of catalytic reactions, including the hydrolysis of organophosphorus nerve agents within seconds in basic aqueous solutions. In addition, postsynthetic modification of Zr-MOFs enables the release of active species capable of reacting with and deactivating harmful pathogens. Despite this impressive performance, utilizing Zr- MOFs in powder form is not practical for application in masks or protective uniforms. To address this challenge, our team sought to develop MOF/fiber composite systems that could be adapted for use under realistic operating conditions to protect civilians, military personnel, and first responders from harmful pathogens and chemical warfare agents. Over the last several years, our group has designed and fabricated reactive and biocidal MOF/fiber composites that effectively capture and deactivate these toxic species. In this Account, we describe the evolution of these porous and reactive MOF/fiber composites and focus on key design challenges and considerations. First, we devised a scalable method for the integration of Zr-MOFs onto textile substrates using aqueous precursor solutions and without using pretreated textiles, highlighting the potential scalability of this method. Moving beyond standard textiles, we also developed a microbial synthesis strategy to prepare hierarchically porous MOF/bacterial cellulose nanofiber composite sponges that can both capture and detoxify nerve agents when exposed to contaminated gas flows. The mass loading of the MOF in the nanofibrous composite sponge is up to 90%, affording higher work capacities compared to those of textile-fiber-based composites with relatively lower MOF loadings. Next, we demonstrated that heterogeneous polymeric bases are suitable replacements for volatile liquid bases typically used in solution-phase reactions, and we showed that these composite systems are capable of effectively hydrolyzing nerve agents in the solid state by using only water that is present as humidity. Moreover, incorporating a reactive dye precursor into the composite affords a dual function sensing and detoxifying material that changes color from white to orange upon reaction with the byproduct following nerve agent hydrolysis, demonstrating the versatility of this platform for use in decontamination applications. We then created chlorine-loaded MOF/fiber composites that act as biocidal and reactive textiles that are capable of not only detoxifying sulfur-mustard-based chemical warfare agents and simulants but also deactivating both bacteria and the SARS-CoV-2 virus within minutes of exposure. Lastly, we synthesized a mixed-metal Ti/Zr-MOF coating on cotton fibers to afford a photoactive biocidal cloth that shows fast and broad-spectrum biocidal performance against viruses and Gram-positive and Gram-negative bacteria under visible light irradiation. Given the tunable, multifunctional nature of these MOF/fiber composites, we believe that this Account will offer new insights for the rational design and preparation of functional MOF/fiber composites and pave the way toward the development of next-generation reactive and protective textiles.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Quasi-Classical Trajectory Calculation of Rate Constants Using an Ab Initio Trained Machine Learning Model (aML-MD) with Multifidelity Data

Machine learning (ML) provides a great opportunity for the construction of models with improved accuracy in classical molecular dynamics (MD). However, the accuracy of a ML trained model is limited by the quality and quantity of the training data. Generating large sets of accurate ab initio training data can require significant computational resources. Furthermore, inconsistent or incompatible data with different accuracies obtained using different methods may lead to biased or unreliable ML models that do not accurately represent the underlying physics. Recently, transfer learning showed its potential for avoiding these problems as well as for improving the accuracy, efficiency, and generalization of ML models using multifidelity data. In this work, ab initio trained ML-based MD (aML-MD) models are developed through transfer learning using DFT and multireference data from multiple sources with varying accuracy within the Deep Potential MD framework. Further, the accuracy of the force field is demonstrated by calculating rate constants for the H + HO 2 → H 2 + 3 O 2 reaction using quasi-classical trajectories. We show that the aML-MD model with transfer learning can accurately predict the rate constants while reducing the computational cost by more than five times compared to the use of more expensive quantum chemistry training data sets. Hence, the aML-MD model with transfer learning shows great potential in using multifidelity data to reduce the computational cost involved in generating the training set for these potentials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Probing Conformational Evolution and Associated Dynamics of Mg(N(SO 2 CF 3 ) 2 ) 2 ·Dimethoxyethane Adduct Using Solid-State 19 F and 1 H NMR

Bis(trifluoromethanesulfonimide) or TFSI is widely used as a counter anion in electrolyte design due to its structural flexibility and chemical stability. Here we studied the conformational variations and associated dynamics of TFSI in adduct of Mg(TFSI) 2 with dimethoxyethane (DME), a solvate crystalline material using solid-state 1 H and 19 F NMR. TFSI molecular motion in this solvate structure falls within the timescale of the 19 F NMR experiment, yielding spectroscopic signatures for unique TFSI conformers under the coordination environment of Mg 2+ cation. Within the temperature range of -5 to 82 °C, we observe nine distinct TFSI sites in both crystalline and disordered regions using 19 F NMR, reflecting complexity of structural and dynamics of TFS1 anions within solvate structure. The four distinguishable sites in the disordered region for the two CF 3 groups of the same TFSI molecule are identified using chemical shift analysis. The exchange rate constants from site to site are calculated through variable temperature 19 F NMR and two-dimensional (2D) exchange spectroscopy (EXSY) experiments, along with respective activation enthalpies using Eyring's formulation. The flip rate of CF 3 around the S-C bond is estimated as ~ 15 s -1 at 8 °C with ΔH ≠ ~ 22 kJ/mol, but the rotation of the entire TFSI is 4.8 s -1 at 8 °C with a significantly greater ΔH ≠ = 98 ± 10 kJ/mol. Furthermore, the slow conversion of trans to cis conformers at a lower temperature (T ≤ 1 °C) in the crystalline region is monitored, with a conversion rate of ~ 2 x 10 -5 s -1 at -5 °C. Density functional theory (DFT)-based calculations were performed to support further the assignment of experimental chemical shifts, and the activation energy E a = 21.1 kJ/mol obtained for the cis to trans transition is consistent with experimental values. The combined set of 19 F and 1 H under both one-dimensional (1D) and 2D NMR methods demonstrated here can be further used for examining electrode-electrolyte interfaces to probe the motions of various constituents that can enable detailed studies of interfacial processes and dynamics. Ultimately, such studies will aid in the design and discovery of interfacial constructs in which directed defect chemistry, chemical moiety distribution, and nanostructure are employed to drive efficient charge transport.

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

Channel Scaling Dependent Photoresponse of Copper-Based Flexible Photodetectors Fabricated Using Laser-Induced Oxidation

Copper (Cu) oxide compounds (Cu x O), which include cupric (CuO) and cuprous (Cu 2 O) oxide, have been recognized as a promising p-channel material with useful photovoltaic properties and superior thermal conductivity. Typically, deposition methods or thermal oxidation can be used to obtain Cu x O. However, these processes are difficult to apply to flexible substrates because plastics have a comparatively low glass transition temperature. Also, additional patterning steps are needed to fabricate applications. In this work, we fabricated a metal–semiconductor–metal photodetector using laser-induced oxidation of thin Cu films under ambient conditions. Raman spectroscopy, scanning electron microscopy–energy-dispersive X-ray spectroscopy, and atomic force microscopy were used to study the composition and morphology of our devices. Moreover, the photoresponse of this device is reported herein. We performed an in-depth analysis of the relationship between the channel size and number of carriers using scanning photocurrent microscopy. The carrier transport behaviors were identified; the photocurrent decreased as the length and width of the channel increased. Furthermore, we verified the suitability of the device as a flexible photodetector using a variety of bending tests. Our in-depth analysis of this Cu-based flexible photodetector could play an important role in understanding the mechanisms of other flexible photovoltaic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Toward Spatial Control of Reaction Selectivity on Photocatalysts Using Area-Selective Atomic Layer Deposition on the Model Dual Site Electrocatalyst Platform

Photocatalytic water splitting is a promising route to low-cost, green H 2 . However, this approach is currently limited in its solar-to-hydrogen conversion efficiency. One major source of efficiency loss is attributed to the high rates of undesired side and back reactions, which are exacerbated by the proximity of neighboring oxidation and reduction sites. Nanoscopic oxide coatings have previously been used to selectively block undesired reactants from reaching active sites; however, a coating encapsulating the entire photocatalyst particle limits activity as it cannot facilitate both half-reactions. In this work, area selective atomic layer deposition (AS-ALD) was used to selectively deposit semipermeable TiO 2 films onto model metallic cocatalysts for enhancing reaction selectivity while maintaining a high overall activity. Pt and Au were used as exemplary reduction and oxidation cocatalyst sites, respectively, where Au was deactivated toward ALD growth through self-assembled thiol monolayers while TiO 2 was coated onto Pt sites. Electroanalytical measurements of monometallic thin film electrodes showed that the TiO 2 -encapsulated Pt effectively suppressed undesired H 2 oxidation and Fe(II)/Fe(III) redox reactions while still permitting the desired hydrogen evolution reaction (HER). A planar model photocatalyst platform containing patterned interdigitated arrays of Au and Pt microelectrodes was further assessed using scanning electrochemical microscopy (SECM), demonstrating the successful use of AS-ALD to enable local reaction selectivity in a dual-reaction-site (photo)electrocatalytic system. Finally, interdigitated microelectrodes having independent potential control were used to show that selectively deposited TiO 2 coatings can suppress the rate of back reactions on neighboring active sites by an order of magnitude compared with uncoated control samples.

08 HYDROGEN↗
DOE OSTI2024

Ion Mobility Separations Using Cocentric Architecture

Ion mobility separations are usually performed in linear channels, which, when extended, can have a large footprint. In this work, we explored the performance of an ion mobility device with a curved architecture which can have a more compact form. The Co-centric Ion Mobility Spectrometer (CIMS) works by manipulating ions between two co-centric surfaces, each containing a serpentine track. The mobility separation inside CIMS is achieved using traveling waveforms (TWs). We initially evaluated the device using ion trajectory simulations using SIMION, which indicated that when ions traveled circularly inside CIMS, they resulted in similar resolving powers and transmitted m/z range as traveling in a straight path in structures for lossless ion manipulations (SLIM). We then performed experimental validation of CIMS in conjunction with a TOF MS. The CIMS was made of 2 flexible printed circuit board materials folded into concentric cylinders separated by a gap of 2.8 mm. The device was about 50 mm diameter × 152 mm long and provided 1.846 m of serpentine path length. Three sets of mixtures (Agilent tune mixture, tetraalkylammonium salts, and 8 peptide mixture) and four traveling waveform profiles (square, sine, triangle, and sawtooth) were used. The sawtooth TW profile produced a slightly higher resolving power for the Agilent tuning mixture and tetraalkylammonium ions. The average resolving power for Agilent tune mixture ions ranged from 37 (using sawtooth TW) to 27 (using square TW). For tetraalkylammonium ions, the average resolving powers ranged from 45 (sawtooth TW) to 31 (square TW). For the peptide mixture ions, the resolving power was similar among the four TW profiles and ranged from 51 to 56. The average percent error in TW CCS for the peptide mixture ions ranged was about 0.4%. In conclusion, the new device showed promising results for a device made of a flexible printed circuit board material, but improvements are needed to further increase the resolving power.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Analyzing Wildland Fire Smoke Emissions Data Using Compositional Data Techniques

By conservation of mass, the mass of wildland fuel that is pyrolyzed and combusted must equal the mass of smoke emissions, residual char and ash. For a given set of conditions, these amounts are fixed. This places a constraint on smoke emissions data which violates statistical assumptions for many of the methods currently used to analyze these data such as linear regression, analysis of variance, and t-tests. These data are inherently multivariate and non-negative parts of a whole. This paper introduces the field of compositional data analysis to the emissions community and provides examples of appropriate statistical treatment of emissions data. It is shown that modified combustion efficiency should not be used as a predictor variable for other smoke emissions because it is not an independent variable. An alternative method based on compositional linear trends to estimate trace gas composition using CO and CO2 is presented. The data used in this paper resulted from projects the DOD/DOE/EPA Strategic 586 Environmental Research and Development Program projects RC-1648 and 1649. The senior 587 author appreciates the guidance and R scripts provided by Prof. Girty at San Diego State 588 University to estimate linear trends by perturbation. J. P.-A. was supported by the Spanish 589 Ministry of Science, Innovation and Universities under the project CODAMET (RTI2018-590 095518-B-C21, 2019-2021). The data used in this study have been previously published and are 591 available in the original publications. DRW conceived the initial manuscript (70 percent) and 592 performed the bulk of the data analysis. JPA provided statistical guidance and compositional data 593 expertise and contributed 20 percent of the manuscript. TJJ and HJ were extensively involved in 594 the study that provided the data. TJJ provide smoke emissions expertise and HJ provided 595 combustion expertise. The authors declare that they have no conflict of interest. The use of trade 596 or firm names in this publication is for reader information and does not imply endorsement by 597 the U.S. Department of Agriculture of any product or service.

simplex, compositional data analysis, balance, log↗
DOE OSTI2022

Tsunami Early Warning From Global Navigation Satellite System Data Using Convolutional Neural Networks

Abstract We investigate the potential of using Global Navigation Satellite System (GNSS) observations to directly forecast full tsunami waveforms in real time. We train convolutional neural networks to use less than 9 min of GNSS data to forecast the full tsunami waveforms over 6 hr at select locations, and obtain accurate forecasts on a test data set. Our training and test data consists of synthetic earthquakes and associated GNSS data generated for the Cascadia Subduction Zone using the MudPy software, and corresponding tsunami waveforms in Puget Sound computed using GeoClaw. We use the same suite of synthetic earthquakes and waveforms as in earlier work where tsunami waveforms were used for forecasting, and provide a comparison. We also explore varying the number of GNSS stations, their locations, and their observation durations.

Rim, Donsub↗
DOE OSTI2025

Using Radiogenic Noble Gas Nuclides to Identify and Characterize Rock Fracturing

Abstract Fracture‐released radiogenic noble gas nuclides are used to identify locations and constrain the volume of new fracture creation during subsurface detonations. Real‐time, in situ noble gases and reactive gases were monitored using a field‐deployed mass spectrometer and automated sampling system in a multilevel borehole array. Released gases were measured after two different detonations having distinct energy, pressure, and gas volume characteristics. Explosive‐derived gases (N 2 O, CO 2 ) and excess radiogenic 4 He and 40 Ar above atmospheric background are used to identify locations of gas transport and new fracture creation after each detonation. Fracture‐released radiogenic 4 He is used to constrain the volume of newly created fractures with a model of helium release from fracturing. Explosive by‐product gas was observed in multiple locations both near and distal to the shot locations for both detonations. Radiogenic 4 He and 40 Ar release from rock damage was observed in locations near the detonation after the second, more powerful detonation. Observed 4 He response is consistent with a model of diffusive release from newly created fractures. Volume of new fractures estimated from the 4 He release ranges from 1 to 5 m 2 with apertures ranging from 0.1 to 1 m. Our results provide evidence that radiogenic noble gases released during fracture creation can be identified at the field scale in real time and used to identify timing and location of fracture creation during deformation events. This technique could be useful in subsurface science and engineering problems where the location and amount of newly created rock fracturing is of interest including fault rupture, mine safety, subsurface detonation monitoring and reservoir stimulation.

58 GEOSCIENCES↗
DOE OSTI2024

Use of Satellite, Surface Observations and Numerical Weather Prediction Model Data to Improve Cloud Base Height and Cloud Base Vertical Velocity Estimation

Cloud base height (CBH) and cloud base vertical velocity (CBVV) are important variables that impact the overall climate in a region as they influence the formulation, longevity, and evolution of clouds. Retrieval of both parameters have long used ground instrumentation (e.g., Doppler lidar (DL), ground base radar); however, retrieving CBH from satellites is particularly challenging given that space-based instruments only observe cloud tops. In this manuscript, CBH is retrieved using a multi-linear regression equation, while CBVV used a random forests model. Both retrievals combine satellite and numerical weather prediction data. The satellite data used are the Visible Infrared Imaging Radiometer Suite imagery, while measurements of CBH and CBVV include DL and radiosonde data at the Southern Great Plains (SGP) Atmospheric Radiation Measurement observatory. Data from 83 summer days (May-August) in 2018–2021 featuring cumulus clouds forced by solar heating were examined and used to train the models, with years 2022–2023 used for validation. Various spatial domains were defined with one large (2.4° longitude by 2.0° latitude) SGP domain being split into smaller sections (smallest being 0.99° and 0.61° longitude and latitude respectably). CBH and CBVV values obtained from the DL as compared to the models show root mean square errors between 150 and 200 m, with CBVV values between 0.45 and 1 ms -1 . Finally, it was found that the CBH formulation performs well over all domains, while the CBVV retrievals become less accurate due to more turbulence being introduced into the observations as the number of DL stations decreases in the smaller domains.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Quantifying UAS Observation Error Variance Used in Data Assimilation Systems and Its Impact on Predictive Skill

Observation error determines the weights of the observations and background state used in data assimilation to generate analyses. Quantifying observation error is critical for the optimal assimilation of observational data sets. Uncrewed Aircraft System (UAS) observations have shown potential benefits in filling observational gaps in the lower atmosphere; however, characterization of their error characteristics has been limited. To optimize the use of UAS observations in numerical weather prediction, UAS observation error is estimated based on the 3‐cornered hat diagnostic approach which uses three independent estimates of the atmospheric state. This approach is applied to data from the 2018 Lower Atmospheric Profiling Studies at Elevation‐a Remotely‐piloted Aircraft Team Experiment field campaign using collocated UAS and rawinsonde observations along with output from a set of convection‐permitting model simulations. The estimated observation error values for UAS temperature, wind, and relative humidity measurements were found to be only weakly dependent on height AGL with mean values equal to 0.5°C, 0.8 m s −1 , and 3%, respectively. Only the newly estimated observation error for temperature differed from that previously used to assimilate commercial aircraft observations into global models (1.0°C). However, using this reduced temperature observation error produced more accurate mesoscale analyses and forecasts of both terrain‐driven flows and convection initiation generated by colliding outflow boundaries within the San Luis Valley of Colorado.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Rare earth metals production using alternative feedstock that eliminates HF

This work reports the successful production of rare earth (RE) metal using Na-RE-F. Presently, RE metals are primarily produced using RE-fluoride due to its higher air and moisture stability compared to RE-chloride. However, its preparation requires the use of corrosive and hazardous chemicals, such as hydrofluoric acid (HF) or ammonium bifluoride (NH 4 HF 2 ). The present study demonstrates that Na-RE-F is an alternative salt to the typically used RE-fluoride. The Na-RE-F for this work is produced via a scalable hydrometallurgical approach using three different RE salts as feedstock, including acetate, nitrate, and chloride. HF is neither used nor generated during the salt preparation process. Furthermore, the Na-RE-F powder dries in air (without dry HF), and only water evolves during the drying process. Analyses of the Na-RE-F show that NaF liberates as a flux during the heating process, which lowers the salt reduction temperature to <900 °C, thus minimizing or eliminating the need for additional flux. Calciothermic reduction of the Na-RE-F salt is successfully employed to obtain RE metal. This work represents a safer, greener, and more widely deployable approach for producing the RE metals needed for permanent magnets which support the transition to a cleaner society through the decarbonization of the transportation industry.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Engineering metal oxidation using epitaxial strain

The oxides of platinum group metals are promising for future electronics and spintronics due to the delicate interplay of spin-orbit coupling and electron correlation energies. However, their synthesis as thin films remains challenging due to their low vapour pressures and low oxidation potentials. Here we show how epitaxial strain can be used as a control knob to enhance metal oxidation. Using Ir as an example, we demonstrate the use of epitaxial strain in engineering its oxidation chemistry, enabling phase-pure Ir or IrO 2 films despite using identical growth conditions. The observations are explained using a density-functional-theory-based modified formation enthalpy framework, which highlights the important role of metal-substrate epitaxial strain in governing the oxide formation enthalpy. We also validate the generality of this principle by demonstrating epitaxial strain effect on Ru oxidation. The IrO 2 films studied in our work further revealed quantum oscillations, attesting to the excellent film quality. The epitaxial strain approach we present could enable growth of oxide films of hard-to-oxidize elements using strain engineering.

36 MATERIALS SCIENCE↗
DOE OSTI2020

High-purity electrolytic lithium obtained from low-purity sources using solid electrolyte

Lithium (Li) is an important resource for the sustainability of socioeconomic systems given its wide use in various industrial applications. The industrial production of Li metals relies on the electrolysis of a mixture consisting of high-purity lithium chloride (LiCl) and potassium chloride. However, the purification of LiCl is expensive and unsustainable, requiring a substantial amount of energy and the use of noxious chemical reagents, so that producing high-purity Li efficiently and sustainably is a challenge. In this paper we report a new method of producing high-purity electrolytic Li from low-purity LiCl using solid-state electrolyte. Taking advantage of the high Li-ion selectivity of the solid electrolyte, we directly obtained high-purity metallic Li through the electrolysis of low-purity LiCl. Our new method provides two important advantages over conventional methods: (1) the cost of producing high-purity Li is reduced by using low-purity LiCl from low-grade brine, and the simpler purification process reduces the use of energy and chemical reagents; and (2) the operating temperature of the electrolytic process decreases from 400 °C to 240 °C, leading to an additional reduction in energy use.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Machine learning enabled quantification of the hydrogen bonds inside the polyelectrolyte brush layer probed using all-atom molecular dynamics simulations

The configuration of densely grafted charged polyelectrolyte (PE) brushes is strongly dictated by the properties and behavior of the counterions that screen the PE brush charges and the solvent molecules (typically water) that solvate the brush molecules and these screening counterions. Only recently, efforts have been made to study the PE brushes atomistically, thereby shedding light on the properties of brush-supported ions and water molecules. However, even for such efforts, there are limitations associated with using a generic definition to estimate certain properties of water and ions inside the brush layer. For example, water–water hydrogen bonds (HBs) will behave differently for locations outside and inside the brush layer, given the fact that the densely closely grafted PE brush molecules create a soft nanoconfinement where the water connectivity becomes highly disrupted: therefore, using the same definition to quantify the HBs inside and outside the brush layer will be unwise. In this paper, we address this limitation by employing an unsupervised machine learning (ML) approach to predict the water–water hydrogen bonding inside a cationic PE brush layer modeled using all-atom molecular dynamics (MD) simulations. Here, the ML method, which relies on a clustering approach and uses the equilibrium coordinates of the water molecules (obtained from the all-atom MD simulations) as the input, is capable of identifying the structural modification of water–water HBs (revealed through appropriate clustering of the data) inside the PE brush layer induced soft nanoconfinement. Such capabilities would not have been possible by using a generic definition of the HBs. Our calculations lead to four key findings: (1) the clusters formed inside and outside the brush layer are structurally similar; (2) the margin of the cluster is shorter inside the PE brush layer confirming the possible disruption of the HBs inside the PE brush layer; (3) the average “hydrogen–acceptor-oxygen–donor-oxygen” angle that defines the HB is reduced for the HBs formed inside the brush layer; (4) the use of the generic definition (definition usable for characterizing the HBs in brush-free bulk) leads to an overprediction of the number of HBs formed inside the PE brush layer.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Using OpenMP for HEP framework algorithm scheduling

The OpenMP standard is the primary mechanism used at high performance computing facilities to allow intra-process parallelization. In contrast, many HEP specific software packages (such as CMSSW, GaudiHive, and ROOT) make use of Intel’s Threading Building Blocks (TBB) library to accomplish the same goal. In these proceedings we will discuss our work to compare TBB and OpenMP when used for scheduling algorithms to be run by a HEP style data processing framework. This includes both scheduling of different interdependent algorithms to be run concurrently as well as scheduling concurrent work within one algorithm. As part of the discussion we present an overview of the OpenMP threading model. We also explain how we used OpenMP when creating a simplified HEP-like processing framework. Using that simplified framework, and a similar one written using TBB, we will present performance comparisons between TBB and different compiler versions of OpenMP.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

A large field-of-view high-resolution hard x-ray microscope using polymer optics

Here, we present an effective approach using a matched pair of polymer-based condenser-objective lenses to build a compact full-field X-ray microscope with a high spatial resolution. A unique condenser comprising arrays of high-aspect-ratio prisms with equilateral cross-section is used for uniformly illuminating samples over a large field of view (FoV) from all angles, which match the acceptance of an objective made of interdigitated orthogonal rows of one-dimensional lenses. State-of-the-art Talbot grating interferometry used to characterize these lenses for the first time revealed excellent focusing properties and minimal wave-front distortions. Using a specific lens-pair designed for 20 keV X-rays, short-exposure times, and image registration with a cross-correlation technique, we circumvent vibrational instabilities to obtain distortion-free images with a uniform resolution of 240 nm (smallest resolvable line pair) over a large FoV, 80 × 80 µm 2 in extent. The results were contrasted with those collected under illumination using commercial two-dimensional parabolic lenses with a smaller FoV. This approach implemented on a diffractometer would enable diffraction-contrast or dark-field microscopy for fast observations of ‘mesoscopic’ phenomena in real space complementing reciprocal-space studies using diffraction on the same instrument.

47 OTHER INSTRUMENTATION↗