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DOE OSTI2016

Automatic Tuning Matching Cycler (ATMC) in situ NMR spectroscopy as a novel approach for real-time investigations of Li- and Na-ion batteries

We have developed and explored the use of a new Automatic Tuning Matching Cycler (ATMC) in situ NMR probe system to track the formation of intermediate phases and investigate electrolyte decomposition during electrochemical cycling of Li- and Na-ion batteries (LIBs and NIBs). The new approach addresses many of the issues arising during in situ NMR, e.g., significantly different shifts of the multi-component samples, changing sample conditions (such as the magnetic susceptibility and conductivity) during cycling, signal broadening due to paramagnetism as well as interferences between the NMR and external cycler circuit that might impair the experiments. We provide practical insight into how to conduct ATMC in situ NMR experiments and discuss applications of the methodology to LiFePO4 (LFP) and Na3V2(PO4)2F3 cathodes as well as Na metal anodes. Automatic frequency sweep 7Li in situ NMR reveals significant changes of the strongly paramagnetic broadened LFP line shape in agreement with the structural changes due to delithiation. Additionally, 31P in situ NMR shows a full separation of the electrolyte and cathode NMR signals and is a key feature for a deeper understanding of the processes occurring during charge/discharge on the local atomic scale of NMR. 31P in situ NMR with “on-the-fly” re-calibrated, varying carrier frequencies on Na3V2(PO4)2F3 as a cathode in a NIB enabled the detection of different P signals within a huge frequency range of 4000 ppm. The experiments show a significant shift and changes in the number as well as intensities of 31P signals during desodiation/sodiation of the cathode. The in situ experiments reveal changes of local P environments that in part have not been seen in ex situ NMR investigations. Furthermore, we applied ATMC 23Na in situ NMR on symmetrical Na–Na cells during galvanostatic plating. An automatic adjustment of the NMR carrier frequency during the in situ experiment ensured on-resonance conditions for the Na metal and electrolyte peak, respectively. Thus, interleaved measurements with different optimal NMR set-ups for the metal and electrolyte, respectively, became possible. This allowed the formation of different Na metal species as well as a quantification of electrolyte consumption during the electrochemical experiment to be monitored. The new approach is likely to benefit a further understanding of Na-ion battery chemistries.

25 ENERGY STORAGE↗

DOE OSTI2022

Numerical and experimental investigation of the flame kernel growth in a methane/air mixture near the lean flammability limit

Lean combustion has the potential to improve the thermal efficiency of spark-ignition engines, but it faces the significant challenge of increased cycle-to-cycle variation due to low mixture reactivity and unstable flame dynamics. Computational fluid dynamics (CFD) employing predictive models can guide engine design and optimize operating strategies for lean combustion. However, ignition and combustion models have rarely been validated at fuel-lean conditions, and a fundamental understanding of the early flame kernel growth process is also lacking for a successful sub-model development. Here, the present study develops a numerical simulation framework used to investigate early flame kernel growth in methane/air mixtures. A nanosecond-pulsed discharge (NPD) approach is employed to effectively decouple the flame kernel growth from the electrical discharge due to their difference in timescales, and equivalence ratios near the experimentally measured lean flammability limit (LFL) are selected to focus on challenging mixture conditions. Three numerical investigations, such as the choice of turbulence modeling, grid size, and grid control strategies, are examined to match both LFL and flame kernel structure measured from experiments. It is demonstrated that a quasi-direct numerical simulation (QDNS) with a fixed grid embedding of 10 μm can predict the LFL as φ CFD =0.61 and match the displacement speed of the kernel’s boundary marked in schlieren images. To predict the LFL and flame kernel shape, a fine grid (Δ≤12.5 μm) is needed to capture the consumption of formaldehyde (CH 2 O) in kernel’s reaction branches attached to the anode, and adaptive mesh refinement is replaced with the fixed embedding due to loss of simulation accuracy. Also, it is found that a large-eddy simulation (LES) using the Dynamic Structure model is not suitable for the NPD-induced flame kernel simulation because artificial sub-grid turbulent kinetic energy induced by shock dynamics alters the flow velocity calculation, resulting in divergence of LES from QDNS. Lastly, the simulation well matches the experimental data for the flame kernel evolution in three mixture conditions (φ = 0.7, 0.61, 0.55), showing toroidal flame kernel expansion and flame kernel growth/extinction.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2025

Effect of particle size and moisture on flow performance of loblolly pine anatomical fractions: Experimental findings and model predictions

The rising energy demand has highlighted biomass as a promising next-generation energy source. However, commercializing biomass-derived energy faces challenges, particularly in handling biomass feedstock. Factors like particle size, shape, moisture content, and surface roughness significantly impact biomass flowability. This study addresses a crucial knowledge gap by examining the effects of particle size and moisture content on the flow behavior and shear properties of different anatomical fractions of loblolly pine (Pinus taeda). The bulk shear behavior was examined using a Schulze ring shear tester, while flow performance was tested through gravity-driven flow experiments in a variable wedge-shape hopper. Results were incorporated into empirical and machine learning-based flow prediction models to evaluate their accuracy and limitations. The study found that samples with higher moisture content show higher unconfined yield strength. The critical arching distance increased with particle size, e.g., from approximately 13 and 33 mm for 2- and 6-mm whole chips, respectively at a 32-degree inclination angle. Conversely, the flow rate decreased for a given hopper opening as particle size increased. For instance, at a 60-mm hopper opening and a 32-degree inclination angle, the mass flow rates for 2- and 6-mm whole chips were 7.83 and 6.42 tonne/h, respectively. The empirical model consistently overpredicted the mass flow rate for all anatomical fractions, while the machine learning model more accurately predicted the central tendency of flow rate but was insensitive to varying tissue proportions. These novel findings provide comprehensive characterization of anatomical fractions, reveal significant combined effects of particle size and moisture content on biomass flow behavior, and demonstrate a better predictive accuracy of a machine learning model, all of which are useful for optimizing material handling strategies and biomass utilization technologies in the industry.

09 - BIOMASS FUELS↗

DOE OSTI2024

ANS Winter 2024 Summary: Optimizing the ATF-2Ramp Power Profile

When the Halden Boiling Water Reactor closed down in 2018, a need to restore the capability for in-reactor power ramp testing arose. Such testing is valuable for studying pellet-clad interaction phenomena in nuclear fuels. The data from these studies is of great interest to a number of research programs, including the accident-tolerant fuel (ATF) program at Idaho National Laboratory (INL). In 2022, Woolstenhulme et al. proposed several power ramp testing ideas using facilities at INL, including irradiation in the Transient Reactor Test Facility (better known as TREAT) and the Advanced Test Reactor (ATR) [1]. Worrall et al. [2] and Labossiere-Hickman et al. [3] subsequently performed feasibility studies for the ATR testing options in 2023. This summary further investigates the three-pin trefoil design (Fig. 1) for the proposed ATF-2Ramp Experiment discussed in Labossiere-Hickman et al. [3]. ATF-2Ramp is designed to operate in the center flux trap (CFT) of the ATR during a powered axial locator mechanism (PALM) cycle: a short, variable-powered cycle with an asymmetric power distribution. Previously, it was shown that tailoring the thickness of the hafnium (Hf) neutron shields (“mini-shrouds”) surrounding each pin offered a degree of control sufficient to achieve the programmatic linear heat generation rate (LHGR) targets for ATF-2Ramp during the high-power period of a PALM cycle. New work involves shortening the experiment test train for consistency with the fuel pins in ATF-2D [4] and then shaping the axial power profile of the three test pins.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Crystallization and Phase Transformations of Aluminum (Oxy)hydroxide Polymorphs in Caustic Aqueous Solution

Gibbsite, bayerite, and boehmite are important aluminum (oxy)hydroxide minerals in nature and have been widely deployed in various industrial applications. They are also major components in caustic nuclear wastes stored at various U.S. locations. Knowledge of their crystallization and phase transformation processes contributes to understanding their occurrence and could help optimize waste treatment processes. While it has been reported that partial conversion of bayerite and gibbsite to boehmite occurs in basic solutions at elevated temperatures, systematic studies of factors affecting the phase transformation as well as the underlying reaction mechanisms are non-existent, particularly in highly alkaline solutions. We explored the effects of sodium hydroxide concentrations (0.1~3 M), reaction temperature (60~100 ?) and aluminum concentrations (0.1~1 M) on the crystallization and transformation of these aluminum (oxy)hydroxides. Detailed structural and morphological characterization by X-ray diffraction (XRD), scanning electron microscopy (SEM), and nuclear magnetic resonance (NMR) spectrometry revealed that these processes depend largely on the reaction temperature and the Al/OH- ratio. When 1 = Al/OH- = 2.5, the reactions favor formation of high crystallinity precipitates, whereas at Al/OH- ratio ? 2.5 precipitation ceases unless the Al concentration is higher than 1 M. We identified pseudoboehmite, bayerite and gibbsite as intermediate phases to bayerite, gibbsite and boehmite, respectively, all of which transform via dissolution-reprecipitation. Gibbsite transforms to boehmite in both acidic and weak caustic environments at temperatures above 80 oC. However, a ‘bar-shaped’ gibbsite morphology dominates in highly caustic environments (3 M NaOH). The findings enable a robust basis for selection of various solid phases by tuning the reaction conditions.

aluminum (oxy)hydroxide polymorphs, crystallizatio↗

DOE OSTI2020

Predicting 3D moisture sorption behavior of materials from 1D investigations

Abstract Moisture in materials can be a source of future outgassing and exacerbate unwanted changes in physical and chemical properties. Here, we investigate the effect of sample size and shape on the moisture transport phenomena through a combined experimental and modeling approach. Several different materials varying in size and shape were investigated over a wide range of relative humidities (0–90%) and temperatures ( $$30{-}70^{\,\circ } \hbox {C}$$ 30 - 70 ∘ C ) using gravimetric type dynamic vapor sorption (DVS). A dynamic triple-mode sorption model, developed previously, was employed to describe the experimental results with good success; the model includes absorption, adsorption, pooling (clustering) of species, and molecular diffusion. Here we show that the full triple-mode sorption model is robust enough to predict the dynamic uptake and outgassing of 3-dimensional (3D) samples using parameters derived from quasi-1D samples. This successful demonstration on three different materials (filled polydimethylsiloxane (PDMS), unfilled PDMS, and ceramic inorganic composite) illustrates that the model is robust at describing the scale-independent physics and chemistry of moisture sorption and diffusion materials. This work demonstrates that while sorption mechanisms manifest in testing of all sample sizes, some of these mechanisms were so subtle that they were overlooked in our initial modeling and assessment, illustrating the importance of multi-scale experiments in the development of robust predictive capabilities. Our study also outlines the challenges and viable solutions for global optimization of a multi-parameter model. The ability to quantify moisture sorption and diffusion, independent of scale, using 1D lab-scale experiments enables prediction of long-term bulk materials behavior in real applications.

36 MATERIALS SCIENCE↗

DOE OSTI2017

The Emergence of Life as a First-Order Phase Transition

It is well known that life on Earth alters its environment over evolutionary and geological timescales. An important open question is whether this is a result of evolutionary optimization or a universal feature of life. In the latter case, the origin of life would be coincident with a shift in environmental conditions. Here in this paper we present a model for the emergence of life in which replicators are explicitly coupled to their environment through the recycling of a finite supply of resources. The model exhibits a dynamic, first-order phase transition from nonlife to life, where the life phase is distinguished by selection on replicators. We show that environmental coupling plays an important role in the dynamics of the transition. The transition corresponds to a redistribution of matter in replicators and their environment, driven by selection on replicators, exhibiting an explosive growth in diversity as replicators are selected. The transition is accurately tracked by the mutual information shared between replicators and their environment. In the absence of successfully repartitioning system resources, the transition fails to complete, leading to the possibility of many frustrated trials before life first emerges. Often, the replicators that initiate the transition are not those that are ultimately selected. The results are consistent with the view that life's propensity to shape its environment is indeed a universal feature of replicators, characteristic of the transition from nonlife to life. We discuss the implications of these results for understanding life's emergence and evolutionary transitions more broadly.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2015

Phonon Sensor Dynamics for Cryogenic Dark Matter Search Experiment

Understanding the quasiparticle diffusion process inside sputtered aluminum (Al thin films (∼ 0.1-1 μm is critical for the Cryogenic Dark Matter Search (CDMS experiment to further optimize its detectors to directly search for dark matter. An initial study with Al films was undertaken by our group ∼ 20 years ago, but some important questions were not answered at the time. This thesis can be considered a continuation of that critical study. The CDMS experiment utilizes high purity silicon and germanium crystals to simultaneously measure ionization and phonons created by particle interactions. In addition to describing some of the rich physics involved in simultaneously detecting ionization and phonons with a CDMS detector, this thesis focuses on the detailed physics of the phonon sensors themselves, which are patterned onto CDMS detector surfaces. CDMS detectors use thin sputtered Al films to collect phonon energy when it propagates to the surfaces of the detector crystals. The phonon energy breaks Cooper pairs and creates quasiparticles (qps). These qps diffuse until they get trapped in an proximitized “overlap” region where lower-Tc tungsten films connect to the Al film. These tungsten films are the transition edge sensors (W-TESs CDMS uses to readout phonon signals. We performed a wide range of experiments using several sets of test devices designed and fabricated specifically for this work. The devices were used mostly to study quasiparticle (qp transport in Al films and qp transmission through Al/W interfaces. The results of this work are being used to optimize the design of detectors for SuperCDMS SNOLAB. This thesis is intended for CDMS collaborators who are interested in knowing more about the detailed fundamentals of how our phonon sensors work so they can take full advantage of their benefits. However, this work can also be read by general readers who are interested in particle detection using TES technology. This thesis contains eight chapters. The first chapter gives basic background information about dark matter and searches for it. We then describe the basic CDMS detector technology in Chapter two. Chapter three focuses on superconductivity and explains some of the solid state physic most relevant to our Al and W film studies. We then turn our attention to the fabrication processes used to make test devices, and describe some of the studies done to characterize our W and Al film properties. Chapter five explains the experimental setup including how a 3He/4He dilution refrigerator works, and how our electronics were configured. We then get to chapter six where we present key experimental results. Chapter seven covers the TES model we used for our test devices to simulate the data pulse shapes and reconstruct the pulse energies. We also describe the diffusion models used to fit our data. Finally, we end with a short summary of our findings and provide a few suggestions for future studies.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2016

Modeling Co-Extruded Cathodes for High Energy Lithium-Ion Batteries

Utilizing an existing macro-homogeneous porous electrode model developed by John Newman, this talk presents the potential energy density gains that can be realized in lithium-ion battery electrodes fabricated with co-extrusion (CoEx) technology. CoEx uses carefully engineered fluidic channels to cause multiple streams of dissimilar fluids to impart shape to one another. The result is a high-speed, continuous deposition process that can create fine linear structures much smaller than the smallest physical feature within the printhead. By eliminating the small channels necessary for conventional extrusion and injection processes, CoEx is able to deposit highly loaded and viscous pastes at high line speeds under reasonable operating pressures. The CoEx process is capable of direct deposition of features as small as 10 μm with aspect ratios of 5 or greater, and print speeds > 80 ft/min. We conduct an analysis on two-dimensional cathode cross-sections in COMSOL and present the electrochemical performance results, including calculated volumetric energy capacity for Lithium Nickel Manganese Cobalt Oxide (NMC) co-extruded cathodes, in the presence of a lithium metal anode, polymer separator and ethylene carbonate–diethyl carbonate (EC:DEC) liquid electrolyte. The impact of structured electrodes on cell performance is investigated by varying the physical distribution of a fixed amount of cathode mass over a space of dimensions which can be fabricated by CoEx. By systematically varying the thickness and aspect ratio of the electrode structures, we present an optimal subset of geometries and design rules for co-extruded geometries. Modeling results demonstrate that NMC CoEx cathodes, on the order of 125-200 µm thick, can garner an improvement in material utilization and in turn capacity through the addition of fine width electrolyte channels or highly conductive electrode regions. We also present initial experimental results on CoEx NMC cathode structures.

25 ENERGY STORAGE↗

DOE OSTI2018

Final Report: Optimal Model Complexity in Geological Carbon Sequestration: A Response Surface Uncertainty Analysis

The critical component of a risk assessment study in evaluating GCS is an analysis of uncertainty in CO2 modeling. In such analyses, direct numerical simulation of CO2 flow and leakage requires many time-consuming model runs. Alternatively, analytical methods have been developed which allow fast and efficient estimation of CO2 storage and leakage, although restrictive assumptions on formation rock and fluid properties are employed. In this study, an intermediate approach is proposed based on the Design of Experiment and Response Surface methodology, which consists of using a limited number of numerical simulations to estimate a prediction outcome as a combination of the most influential uncertain site properties. The methodology can be implemented within a Monte Carlo framework to efficiently assess parameter and prediction uncertainty while honoring the accuracy of numerical simulations. The choice of the uncertain properties is flexible and can include geologic parameters that influence reservoir heterogeneity, engineering parameters that influence gas trapping and migration, and reactive parameters that influence the extent of fluid/rock reactions. The method was tested and verified on modeling long-term CO2 flow, non-isothermal heat transport, and CO2 dissolution storage by coupling two-phase flow with explicit miscibility calculation using an accurate equation of state that gives rise to convective mixing of formation brine variably saturated with CO2. All simulations were performed using three-dimensional high-resolution models including a target deep saline aquifer, overlying caprock, and a shallow aquifer. To evaluate the uncertainty in representing reservoir permeability, sediment hierarchy of a heterogeneous digital stratigraphy was mapped to create multiple irregularly shape stratigraphic models of decreasing geologic resolutions: heterogeneous (reference), lithofacies, depositional environment, and a (homogeneous) geologic formation. To ensure model equivalency, all the stratigraphic models were successfully upscaled from the reference heterogeneous model for bulk flow and transport predictions (Zhang & Zhang, 2015). GCS simulation was then simulated with all models, yielding insights into the level of parameterization complexity that is needed for the accurate simulation of reservoir pore pressure, CO2 storage, leakage, footprint, and dissolution over both short (i.e., injection) and longer (monitoring) time scales. Important uncertainty parameters that impact these key performance metrics were identified for the stratigraphic models as well as for the heterogeneous model, leading to the development of reduced/simplified models at lower characterization cost that can be used for the reservoir uncertainty analysis. All the CO2 modeling was conducted using PFLOTRAN – a massively parallel, multiphase, multi-component, and reactive transport simulator developed by a multi-laboratory DOE/SciDAC (Scientific Discovery through Advanced Computing) project (Zhang et al., 2017, in review). Within the uncertainty analysis framework, increasing reservoir depth were investigated to explore its effect on the uncertainty outcomes and the potential for developing gravity-stable injection with increased storage security (Dai et al., 20126; Dai et al., 2017, in review). Finally, to accurately model CO2 fluid-rock reactions and resulting long-term storage as secondary carbonate minerals, a modified kinetic rate law for general mineral dissolution and precipitation was proposed and verified that is invariant to a scale transformation of the mineral formula weight. This new formulation will lead to more accurate assessment of mineral storage over geologic time scales (Lichtner, 2016).

58 GEOSCIENCES↗

DOE OSTI2024

Design and Development of a Fixtureless, Pass-through Machine Tool for Extrusion Machining

The aerospace, construction/architecture, and transportation manufacturing industries rely heavily on the mass production of near-net shape metallic and composite extrusions. While the production of raw extrusions is a relatively fast process, adding functional features such as holes and slots require additional time, cost, and energy to produce. To compensate for the inherent flexibility of extrusions, conventional machining requires rigid purpose-built fixtures for operations such as trimming, drilling and thinning. This approach requires that the machine tools be as large or larger than the parts themselves. This results in the need for excess shop floor space, energy for auxiliary equipment and motion systems, and significant capital expenditure. Considerable engineering expense and time involved in the designing, building, and proving out of part-specific fixtures for holding the components in specific configurations while machining add to the overall manufacturing cost. The primary objective of the technical collaboration between Oak Ridge National Laboratory and Fairmount Technologies (FT) is to improve the XM-3, a fixtureless CNC milling machine designed by FT. The machine was developed to trim, drill, and thin extrusions without part specific fixturing to make the manufacturing process more efficient and flexible. Dynamic measurements of the existing structure were collected, and modeling efforts were made to evaluate optimal machining parameters for the current system. Areas of improvement to increase the system stiffness, manufacturability, and machining efficiency were evaluated and highlighted for the next generation design. The impact of this effort may enable agile manufacturing across the commercial and defense aerospace industries, and other industries where extrusions are utilized like in the construction, architecture, and transportation industries.

42 ENGINEERING↗

DOE OSTI2025

Design and Development of a Fixtureless, Pass-through Machine Tool for Extrusion Machining

42 ENGINEERING↗

DOE OSTI2022

PM4Stell: A prototype permanent magnet stellarator structure

Permanent magnets provide a possible solution to simplify complicated stellarator coils. Here, a prototype permanent magnet stellarator structure, PM4Stell, has been funded to demonstrate the technical feasibility of using permanent magnets to create the shaping field of a stellarator. Permanent magnets in uniform cubes with three polarization directions will be carefully placed to generate the required magnetic field for a National Compact Stellarator eXperiment-like equilibrium together with planar toroidal field coils. Discrete magnets will be glued together and inserted into a “post-office-box-like” supporting structure. Electromagnetic and structural analyses have been done to validate the design. Error field correction magnets will be used to shim possible error fields. The design efforts of the prototype permanent magnet stellarator structure are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Pilot Testing of a Modular Oxygen Production System Using Oxygen Binding Adsorbents (Final Report)

In this project, RTI and Air Liquide have focused on the development of innovative oxygen separation materials and technologies based on reversibly binding of oxygen to enable smaller and cheaper air separations. In alignment with that object the team has had multiple achievements to advance the technology including: Synthesized and characterized novel M-CoSalen (RTIO2Sorb-1) material which showed a dynamic oxygen adsorption capacity in excess of 1wt%. Developed synthesis routes for RTIO2Sorb-1 with commercially relevant techniques and produced batches of 0.25kg and over 4 kg of total synthesis. Synthesized and characterized extrudate forms of the RTIO2Sorb-1 with relevant crush strength and maintained dynamic oxygen adsorption capacity in near 1wt%. Developed techniques for forming structured beds in fiber shapes with conventional materials. Developed a model for O 2 sorption processes to analyze various bed configurations and cycle parameters. Studied classic O 2 solid sorbents reported in the literature to learn oxygen binding mechanisms. Design a 10 kg/day O 2 VPSA pilot system with 2 or 4-bed operation. Completed a techno-economic analysis based on the experimental results and modeling. The overall objective of the project was to design, fabricate, and test a modular O 2 production system and perform a techno-economic analysis (TEA) after testing to determine the cost-benefit of the advanced modular air separation system. The goals of this technology development project were to achieve a bed-size factor (BSF) of less than 600 lb-adsorbent/TPD O 2 (ton/day O 2 ) (as compared with the state-of-the-art BSF of 850), and O 2 -purity greater than 95% at a cost that is projected to be equivalent or lower than the current state of the art (SOTA), commercially available large-scale cryogenic air separation systems. To achieve these goals and objective, the project team executed on (1) oxygen binding adsorbent optimization and scale up, (2) adsorbent material formation process studies to form the adsorbent material into structured beds for rapid pressure swing adsorption (PSA) cycles with low pressure drop, fast mass transfer, and low attrition, (3) cycle development studies to optimize the PSA process, and (4) develop simulation tools for rapid cycle modeling and numerical evaluation/optimization.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2024

ASMS 2024 Investigation of Uranyl Perchlorate Anion Complexes in the Gas Phase via Infrared Multiphoton Dissociation and Collision Induced Dissociation

Investigation of Uranyl Perchlorate Anion Complexes in the Gas Phase via Infrared Multiphoton Dissociation and Collision Induced Dissociation Brittany D. M. Hodges, Christopher A. Zarzana, JungSoo Kim, Jonathan Martens, and W. C. M. Berden Introduction (120 words max) Effects of electronic structure on chemical bonding and reactivity play critical roles shaping the chemical bonding and reactivity behaviors of heavy elements. Understanding the role of f electrons in bond formation between the actinide-series elements like uranium with other ligands is critical for solving technical challenges associated with these heavy elements, important to nuclear fuel cycles, efficient separations of rare earth metals, and understanding the chemistry of stored nuclear fuels and related environmental management sites. In this study, we further examine the interactions between uranyl and the perchlorate ion in order to understand the structures of these ions through the use of IRMPD. Here we report the IRMPD spectra of [UO2(ClO4)3]-, [UO3(ClO4)2]-, and a proposed transition state. Methods (120 word max) IRMPD spectra and CID spectra were acquired using a Bruker amaZon QIT/MS instrument at the Free-Electron Lasers for Infrared eXperiments (FELIX) laboratory at Radboud University. The FELIX QIT/MS is modified to allow for the high-intensity tunable IR beam from FELIX to be directed into the ion packet, resulting in multiphoton dissociation that is measured only when the IR frequency is in resonance with an adequately high absorption vibrational mode of the mass-selected complex. DFT geometry optimizations and frequency calculations using the Gaussian suite of programs were performed using B3LYP, TPSSh, and PBE0 level of theory with 6-31+G(d) basis for the O, C, H, and N atoms and the SDD basis set for U. The SDD basis set employs the Stuttgart/Dresden effective core potential. Preliminary Data or Plenary Speakers Abstract (300 words max) Metal ion clusters of uranyl perchlorate were formed via direct electrospray ionization. For each metal ligand complex of interest, the parent ion was isolated and collision induced dissociation fragmentation and Infrared Multiphoton Dissociation (IRMPD) fragmentation spectra were acquired. Results presented here are the first look at the IRMPD spectra of [UO3(ClO4)2]-, [UO2(ClO4)3]-. Structures were examined using Gaussian at different levels of theory B3LYP level of theory, TPPSh and PBE0 levels, to reflect the behaviors of uranium metal ligand complexes most accurately. In these structures, we identified an overlap between each of these uranyl stretches resulting in their largely being obscured by a perchlorate mode. The CID product spectra agree with similar structures reported by Groenewold for uranyl nitrate in 2006 (10.1021/ja058106n).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Bifurcation, chaos, and scan instability in dynamic atomic force microscopy

The dynamical motion at any point on the cantilever of an atomic force microscope can be expressed quite generally as a superposition of simple harmonic oscillators corresponding to the vibrational modes allowed by the cantilever shape. Central to the dynamical equations is the representation of the cantilever-sample interaction force as a polynomial expansion with coefficients that account for the interaction force “stiffness,” the cantilever-to-sample energy transfer, and the displacement amplitude of cantilever oscillation. Renormalization of the cantilever beam model shows that for a given cantilever drive frequency cantilever dynamics can be accurately represented by a single nonlinear mass-spring model with frequency-dependent stiffness and damping coefficients [S. A. Cantrell and J. H. Cantrell, J. Appl. Phys. 110, 094314 (2011)]. Application of the Melnikov method to the renormalized dynamical equation is shown to predict a cascade of period doubling bifurcations with increasing cantilever drive force that terminates in chaos. The threshold value of the drive force necessary to initiate bifurcation is shown to depend strongly on the cantilever setpoint and drive frequency, effective damping coefficient, nonlinearity of the cantilever-sample interaction force, and the displacement amplitude of cantilever oscillation. The model predicts the experimentally observed interruptions of the bifurcation cascade for cantilevers of sufficiently large stiffness. Operational factors leading to the loss of image quality in dynamic atomic force microscopy are addressed, and guidelines for optimizing scan stability are proposed using a quantitative analysis based on system dynamical parameters and choice of feedback loop parameter.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

Scalable and Energy-Efficient Methods for Interactive Exploration of Scientific Data

The main scientific contributions of this project are the following novel concepts for multidimensional arrays: shape-based similarity join (SIGMOD 2016), incremental view maintenance (SIGMOD 2017), user-defined stencil functions (HPDC 2017), and distributed caching for in-situ processing (SSDBM 2018). Building on our collaboration with the astrophysics group at LBNL, we applied these techniques to the data generated in the Palomar Transient Factory (PTF) astronomical survey. They played a pivotal role in the first-ever observation of a neutron star merger, which produces gravitational waves and turns out to be the origin of heavy elements, including gold. This has lead to a Science magazine article that has received extensive media coverage on ACM TechNews, Slashdot, FiveThirtyEight, and Quanta Magazine, among others. Additionally, two other articles detailing related aspects of the same discovery have been published in the Astrophysical Journal Letters journal. These publications have more than 3,000 citations according to Google Scholar (as of February 2022). This cross-disciplinary collaboration provided very good opportunities to apply database techniques to real-life scientific problems. The fact that they facilitated major discoveries in astrophysics proves the importance of our research. In addition to the work on multidimensional array databases, this project has also developed stochastic gradient descent (SGD) optimization algorithms for training large scale machine learning models, methods for querying in-situ data, and a database query optimizer based on sketch synopses.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2017

Roofline Analysis in the Intel® Advisor to Deliver Optimized Performance for applications on Intel® Xeon Phi™ Processor

In this session we show, in two case studies, how the roofline feature of Intel Advisor has been utilized to optimize the performance of kernels of the XGC1 and PICSAR codes in preparation for Intel Knights Landing architecture. The impact of the implemented optimizations and the benefits of using the automatic roofline feature of Intel Advisor to study performance of large applications will be presented. This demonstrates an effective optimization strategy that has enabled these science applications to achieve up to 4.6 times speed-up and prepare for future exascale architectures. # Goal/Relevance of Session The roofline model [1,2] is a powerful tool for analyzing the performance of applications with respect to the theoretical peak achievable on a given computer architecture. It allows one to graphically represent the performance of an application in terms of operational intensity, i.e. the ratio of flops performed and bytes moved from memory in order to guide optimization efforts. Given the scale and complexity of modern science applications, it can often be a tedious task for the user to perform the analysis on the level of functions or loops to identify where performance gains can be made. With new Intel tools, it is now possible to automate this task, as well as base the estimates of peak performance on measurements rather than vendor specifications. The goal of this session is to demonstrate how the roofline feature of Intel Advisor can be used to balance memory vs. computation related optimization efforts and effectively identify performance bottlenecks. A series of typical optimization techniques: cache blocking, structure refactoring, data alignment, and vectorization illustrated by the kernel cases will be addressed. # Description of the codes ## XGC1 The XGC1 code [3] is a magnetic fusion Particle-In-Cell code that uses an unstructured mesh for its Poisson solver that allows it to accurately resolve the edge plasma of a magnetic fusion device. After recent optimizations to its collision kernel [4], most of the computing time is spent in the electron push (pushe) kernel, where these optimization efforts have been focused. The kernel code scaled well with MPI+OpenMP but had almost no automatic compiler vectorization, in part due to indirect memory addresses and in part due to low trip counts of low-level loops that would be candidates for vectorization. Particle blocking and sorting have been implemented to increase trip counts of low-level loops and improve memory locality, and OpenMP directives have been added to vectorize compute-intensive loops that were identified by Advisor. The optimizations have improved the performance of the pushe kernel 2x on Haswell processors and 1.7x on KNL. The KNL node-for-node performance has been brought to within 30% of a NERSC Cori phase I Haswell node and we expect to bridge this gap by reducing the memory footprint of compute intensive routines to improve cache reuse. ## PICSAR is a Fortran/Python high-performance Particle-In-Cell library targeting at MIC architectures first designed to be coupled with the PIC code WARP for the simulation of laser-matter interaction and particle accelerators. PICSAR also contains a FORTRAN stand-alone kernel for performance studies and benchmarks. A MPI domain decomposition is used between NUMA domains and a tile decomposition (cache-blocking) handled by OpenMP has been added for shared-memory parallelism and better cache management. The so-called current deposition and field gathering steps that compose the PIC time loop constitute major hotspots that have been rewritten to enable more efficient vectorization. Particle communications between tiles and MPI domain has been merged and parallelized. All considered, these improvements provide speedups of 3.1 for order 1 and 4.6 for order 3 interpolation shape factors on KNL configured in SNC4 quadrant flat mode. Performance is similar between a node of cori phase 1 and KNL at order 1 and better on KNL by a factor 1.6 at order 3 with the considered test case (homogeneous thermal plasma).

97 MATHEMATICS AND COMPUTING↗