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DOE OSTI2020

Impact of pellet preparation on reflectance measurements of ammonium sulfate by single-angle reflectance spectroscopy

The optical constants, n and k, are required to model the reflection, refraction and transmission of light at the first surface interface of a material, as well as its propagation through the material; here n corresponds to the real component and k the imaginary component of the refractive index. Several different spectroscopic methods have been used to determine the n and k values for different materials, including single angle reflectance spectroscopy and ellipsometry. The single-angle reflectance method quantitatively records the specular reflectance R(v) from a plane parallel face of the material and uses the Kramers-Kronig transform to extract the n and k values. For most compounds, however, it is difficult to obtain a single crystal or high-quality window of sufficient planarity and of the appropriate dimensions (several mm) to make the measurement. For this reason, we further investigate the use of pressed pellets of neat powdered substances to measure optical constants of these substances using the single-angle reflectance method. We have found that surface roughness can significantly influence the measured quantitative reflectance spectrum R(v) and, consequently, the derived n and k parameters. A collaborative study between Defence Research and Development Canada (DRDC) - Valcartier Research Center and Pacific Northwest National Laboratory (PNNL) has been carried out using different pellets of neat ammonium sulfate [(NH4)2SO4] to show how parameters such as the relative fraction of particle sizes for the component powder along with the grinding process of the pure compound all can affect the reflectance spectrum used to derive the optical constants. All pressed pellets were characterized by single-angle reflectance spectroscopy.

Diaz, Emmanuela↗

DOE OSTI2022

Sensor assemblies and methods for emulating interaction of entities within water systems

Sensor assemblies are provided for use in modeling water systems. These sensor assemblies can be used as sensor fish. These assemblies can include a circuit board supporting processing circuitry components on either or both opposing component support surfaces of the circuit board and a housing above the circuit board and the components, with the housing being circular about the circuit board in at least one cross section, and wherein the supporting surfaces of the circuit board are substantially parallel with the plane of the housing in the one cross section. Methods for emulating interaction of entities within water systems are provided. The methods can include introducing a sensor assembly into a water system. The sensor assembly can include: a circuit board supporting processing circuitry components on either or both of opposing component support surfaces of the circuit board; a housing about the circuit board and the components, the housing being circular about the circuit board in at least one cross section; and wherein the support surfaces of the circuit board are substantially parallel with the plane of the housing in the one cross section.

Deng, Z. Daniel↗

DOE OSTI2015

Nitrogen-modified nano-titania: True phase composition, microstructure and visible-light induced photocatalytic NO{sub x} abatement

Titanium dioxide (TiO{sub 2}) is a popular photocatalyst used for many environmental and anti-pollution applications, but it normally operates under UV light, exploiting ∼5% of the solar spectrum. Nitrification of titania to form N-doped TiO{sub 2} has been explored as a way to increase its photocatalytic activity under visible light, and anionic doping is a promising method to enable TiO{sub 2} to harvest visible-light by changing its photo-absorption properties. In this paper, we explore the insertion of nitrogen into the TiO{sub 2} lattice using our green sol–gel nanosynthesis method, used to create 10 nm TiO{sub 2} NPs. Two parallel routes were studied to produce nitrogen-modified TiO{sub 2} nanoparticles (NPs), using HNO{sub 3}+NH{sub 3} (acid-precipitated base-peptised) and NH{sub 4}OH (totally base catalysed) as nitrogen sources. These NPs were thermally treated between 450 and 800 °C. Their true phase composition (crystalline and amorphous phases), as well as their micro-/nanostructure (crystalline domain shape, size and size distribution, edge and screw dislocation density) was fully characterised through advanced X-ray methods (Rietveld-reference intensity ratio, RIR, and whole powder pattern modelling, WPPM). As pollutants, nitrogen oxides (NO{sub x}) are of particular concern for human health, so the photocatalytic activity of the NPs was assessed by monitoring NO{sub x} abatement, using both solar and white-light (indoor artificial lighting), simulating outdoor and indoor environments, respectively. Results showed that the onset of the anatase-to-rutile phase transformation (ART) occurred at temperatures above 450 °C, and NPs heated to 450 °C possessed excellent photocatalytic activity (PCA) under visible white-light (indoor artificial lighting), with a PCA double than that of the standard P25 TiO{sub 2} NPs. However, higher thermal treatment temperatures were found to be detrimental for visible-light photocatalytic activity, due to the effects of four simultaneous occurrences: (i) loss of OH groups and water adsorbed on the photocatalyst surface; (ii) growth of crystalline domain sizes with decrease in specific surface area; (iii) onset and progress of the ART; (iv) the increasing instability of the nitrogen in the titania lattice. - Graphical abstract: Nitrogen modified TiO{sub 2} synthesised via a green aqueous sol–gel method showed to degrade nitrogen oxides (NO{sub x}) under visible white-light (indoor artificial lighting), with a photocatalytic activity double than that of the standard P25 TiO{sub 2} NPs. - Highlights: • N–TiO{sub 2} synthesised via a green aqueous sol–gel method. • Advanced X-ray methods used to detect both crystalline and amorphous contents. • Microstructure fully addressed via XRPD and whole powder pattern modelling. • Photocatalytic NO{sub x} removal assessed using both solar and visible-light lamps.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Virtual Time III, Part 1: Unified Virtual Time Synchronization for Parallel Discrete Event Simulation

Algorithms for synchronization of parallel discrete event simulation have historically been divided between conservative methods that require lookahead but not rollback, and optimistic methods that require rollback but not lookahead. In this paper we present a new approach in the form of a framework called Unified Virtual Time (UVT) that unifies the two approaches, combining the advantages of both within a single synchronization theory. Whenever timely lookahead information is available, a logical process (LP) executes conservatively using an irreversible event handler. When lookahead information is not available the LP does not block, as it would in a classical conservative execution, but instead executes optimistically using a reversible event handler. The switch from conservative to optimistic synchronization and back is decided on an event-by-event basis by the simulator, transparently to the model code. UVT treats conservative synchronization algorithms as optional accelerators for an underlying optimistic synchronization algorithm, enabling the speed of conservative execution whenever it is applicable, but otherwise falling back on the generality of optimistic execution. We describe UVT in a novel way, based on fundamental invariants, monotonicity requirements, and synchronization rules. UVT permits zero-delay messages and pays careful attention to tie-handling using superposition. We prove that under fairly general conditions a UVT simulation always makes progress in virtual time. This is Part 1 of a trio of papers describing the UVT framework for PDES, mixing conservative and optimistic synchronization and integrating throttling control.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Recovering noise-free quantum observables

We introduce a technique for recovering noise-free observables in noisy quantum systems by combining the results of many slightly different experiments. Our approach is applicable to a variety of quantum systems, but we illustrate it with applications to quantum information and quantum sensing. The approach corresponds to repeating the same quantum evolution many times with known variations on the underlying systems' error properties, e.g., the spontaneous emission and dephasing times $T_1$ and $T_2$. As opposed to standard quantum error correction methods, which have an overhead in the number of qubits (many physical qubits must be added for each logical qubit), our method has only an overhead in the number of evaluations, allowing the overhead to, in principle, be hidden via parallelization. We show that the effective spontaneous emission $T_1$ and dephasing $T_2$ times can be increased using this method in both simulation and experiments on an actual quantum computer. We also show how to correct more complicated entangled states and how Ramsey fringes relevant to quantum sensing can be significantly extended in time.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2017

Decentralized Interleaving of Paralleled Dc-Dc Buck Converters: Preprint

We present a decentralized control strategy that yields switch interleaving among parallel connected dc-dc buck converters without communication. The proposed method is based on the digital implementation of the dynamics of a nonlinear oscillator circuit as the controller. Each controller is fully decentralized, i.e., it only requires the locally measured output current to synthesize the pulse width modulation (PWM) carrier waveform. By virtue of the intrinsic electrical coupling between converters, the nonlinear oscillator-based controllers converge to an interleaved state with uniform phase-spacing across PWM carriers. To the knowledge of the authors, this work represents the first fully decentralized strategy for switch interleaving of paralleled dc-dc buck converters.

14 SOLAR ENERGY↗

DOE OSTI2025

OpenSn: A massively parallel, open-source simulation environment for discrete ordinates radiation transport

OpenSn is an open-source, massively parallel deterministic radiation transport code for solving the discrete-ordinates ( S N ) form of the Boltzmann transport equation on unstructured, arbitrary polyhedral meshes. It supports high-fidelity simulations involving steady-state, eigenvalue, and adjoint problems for neutral particles (e.g., neutrons, photons, multi-particles), using the multigroup approximation in energy. OpenSn combines angular discretization via discrete ordinates with a discontinuous Galerkin finite element method (DGFEM) in space, enabling accurate resolution of transport physics on arbitrary polyhedral cells, included locally refined spatial grids. It includes multiple angular quadrature types, including locally refined angular quadratures. Written in modern C++ with a Python API, OpenSn runs efficiently on platforms ranging from laptops to supercomputers. The transport sweep algorithm is implemented using a task-based, directed-acyclic-graph (DAG) approach for each angle and supports asynchronous parallelism across thousands of MPI ranks. Group-set aggregation improves compute intensity, and synthetic acceleration techniques (e.g., diffusion synthetic acceleration, second-moment method) enhance solver convergence. OpenSn has been verified on reactor physics problems and demonstrated excellent weak and strong scaling performance on more than 32,768 processes, making it a versatile and robust platform for large-scale transport simulations in complex geometries.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

Understanding performance variability in standard and pipelined parallel Krylov solvers

In this work, we collect data from runs of Krylov subspace methods and pipelined Krylov algorithms in an effort to understand and model the impact of machine noise and other sources of variability on performance. We find large variability of Krylov iterations between compute nodes for standard methods that is reduced in pipelined algorithms, directly supporting conjecture, as well as large variation between statistical distributions of runtimes across iterations. Based on these results, we improve upon a previously introduced nondeterministic performance model by allowing iterations to fluctuate over time. We present our data from runs of various Krylov algorithms across multiple platforms as well as our updated non-stationary model that provides good agreement with observations. We also suggest how it can be used as a predictive tool.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

System and method for continuous solids slurry depressurization

A continuous slag processing system includes a rotating parallel disc pump, coupled to a motor and a brake. The rotating parallel disc pump includes opposing discs coupled to a shaft, an outlet configured to continuously receive a fluid at a first pressure, and an inlet configured to continuously discharge the fluid at a second pressure less than the first pressure. The rotating parallel disc pump is configurable in a reverse-acting pump mode and a letdown turbine mode. The motor is configured to drive the opposing discs about the shaft and against a flow of the fluid to control a difference between the first pressure and the second pressure in the reverse-acting pump mode. The brake is configured to resist rotation of the opposing discs about the shaft to control the difference between the first pressure and the second pressure in the letdown turbine mode.

36 MATERIALS SCIENCE↗

DOE OSTI2014

Toward enabling large-scale open-shell equation-of-motion coupled cluster calculations: triplet states of β-carotene

In this paper we discuss the application of novel parallel implementation of the coupled cluster (CC) and equation-of-motion coupled cluster methods (EOMCC) in calculations of excitation energies of triplet states in beta-carotene. Calculated excitation energies are compared with experimental data, where available. We also provide a detailed description of the new parallel algorithms for iterative CC and EOMCC models involving single and doubles excitations.

beta-carotene↗

DOE OSTI2017

Robust determination of the chemical potential in the pole expansion and selected inversion method for solving Kohn-Sham density functional theory

Fermi operator expansion (FOE) methods are powerful alternatives to diagonalization type methods for solving Kohn-Sham density functional theory (KSDFT). One example is the pole expansion and selected inversion (PEXSI) method, which approximates the Fermi operator by rational matrix functions and reduces the computational complexity to at most quadratic scaling for solving KSDFT. Unlike diagonalization type methods, the chemical potential often cannot be directly read off from the result of a single step of evaluation of the Fermi operator. Hence multiple evaluations are needed to be sequentially performed to compute the chemical potential to ensure the correct number of electrons within a given tolerance. This hinders the performance of FOE methods in practice. In this paper, we develop an efficient and robust strategy to determine the chemical potential in the context of the PEXSI method. The main idea of the new method is not to find the exact chemical potential at each self-consistent-field (SCF) iteration but to dynamically and rigorously update the upper and lower bounds for the true chemical potential, so that the chemical potential reaches its convergence along the SCF iteration. Instead of evaluating the Fermi operator for multiple times sequentially, our method uses a two-level strategy that evaluates the Fermi operators in parallel. In the regime of full parallelization, the wall clock time of each SCF iteration is always close to the time for one single evaluation of the Fermi operator, even when the initial guess is far away from the converged solution. We demonstrate the effectiveness of the new method using examples with metallic and insulating characters, as well as results from ab initio molecular dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

Chemical detection system and related methods

A chemical detection system includes a frame, an emitter coupled to the frame, and a detector coupled to the frame proximate the emitter. The system also includes a shielding system coupled to the frame and positioned at least partially between the emitter and the detector, wherein the frame positions a sensing surface of the detector in a direction substantially parallel to a plane extending along a front portion of the frame. A method of analyzing composition of a suspect object includes directing neutrons at the object, detecting gamma rays emitted from the object, and communicating spectrometer information regarding the gamma rays. The method also includes presenting a GUI to a user with a dynamic status of an ongoing neutron spectroscopy process. The dynamic status includes a present confidence for a plurality of compounds being present in the suspect object responsive to changes in the spectrometer information during the ongoing process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

Comprehensive sequence-flux mapping of a levoglucosan utilization pathway in E. coli

Synthetic metabolic pathways often suffer from low specific productivity, and new methods that quickly assess pathway functionality for many thousands of variants are urgently needed. Here we present an approach that enables the rapid and parallel determination of sequence effects on flux for complete gene-encoding sequences. We show that this method can be used to determine the effects of over 8000 single point mutants of a pyrolysis oil catabolic pathway implanted in Escherichia coli . Experimental sequence-function data sets predicted whether fitness-enhancing mutations to the enzyme levoglucosan kinase resulted from enhanced catalytic efficiency or enzyme stability. A structure of one design incorporating 38 mutations elucidated the structural basis of high fitness mutations. One design incorporating 15 beneficial mutations supported a 15-fold improvement in growth rate and greater than 24-fold improvement in enzyme activity relative to the starting pathway. Lastly, this technique can be extended to improve a wide variety of designed pathways.

09 BIOMASS FUELS↗

DOE OSTI2018

Scalable hierarchical PDE sampler for generating spatially correlated random fields using nonmatching meshes: Scalable hierarchical PDE sampler using nonmatching meshes

This work describes a domain embedding technique between two nonmatching meshes used for generating realizations of spatially correlated random fields with applications to large-scale sampling-based uncertainty quantification. The goal is to apply the multilevel Monte Carlo (MLMC) method for the quantification of output uncertainties of PDEs with random input coefficients on general and unstructured computational domains. We propose a highly scalable, hierarchical sampling method to generate realizations of a Gaussian random field on a given unstructured mesh by solving a reaction–diffusion PDE with a stochastic right-hand side. The stochastic PDE is discretized using the mixed finite element method on an embedded domain with a structured mesh, and then, the solution is projected onto the unstructured mesh. This work describes implementation details on how to efficiently transfer data from the structured and unstructured meshes at coarse levels, assuming that this can be done efficiently on the finest level. We investigate the efficiency and parallel scalability of the technique for the scalable generation of Gaussian random fields in three dimensions. An application of the MLMC method is presented for quantifying uncertainties of subsurface flow problems. Here, we demonstrate the scalability of the sampling method with nonmatching mesh embedding, coupled with a parallel forward model problem solver, for large-scale 3D MLMC simulations with up to 1.9·109 unknowns.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

A general approach to seismic inversion with automatic differentiation

Imaging Earth structure or seismic sources from seismic data involves minimizing a target misfit function, and is commonly solved through gradient-based optimization. The adjoint-state method has been developed to compute the gradient efficiently; however, its implementation can be time-consuming and difficult. We develop a general seismic inversion framework to calculate gradients using reverse-mode automatic differentiation. The central idea is that adjoint-state methods and reverse-mode automatic differentiation are mathematically equivalent. Here, the mapping between numerical PDE simulation and deep learning allows us to build a seismic inverse modeling library, ADSeismic, based on deep learning frameworks, which supports high performance reverse-mode automatic differentiation on CPUs and GPUs. We demonstrate the performance of ADSeismic on inverse problems related to velocity model estimation, rupture imaging, earthquake location, and source time function retrieval. ADSeismic has the potential to solve a wide variety of inverse modeling applications within a unified framework.

58 GEOSCIENCES↗

DOE OSTI2020

Metastable solubility and local structure of amorphous calcium carbonate (ACC)

The properties of amorphous calcium carbonate provide the foundation for understanding mineralization of calcified skeletons but inconsistencies between studies suggest the physical picture is incomplete. This study quantifies the metastable solubility and structure of ACC produced under a series of chemical conditions. Using complementary in situ methods that quantify ACC structure (in situ PDF analysis) in parallel with chemical composition (TGA, ICP-OES), we find two short-range structures are produced that also show distinct morphological differences. Conditions with high carbonate ion concentrations stabilize a Ca-rich ACC with short-range order that is independent of Mg content. In contrast, low carbonate solutions favor Mg-rich ACC with mixed Ca- and Mg-short range order. Measurements of solubility product determined from supersaturated and undersaturated conditions find the distinctive structures are related to solution carbonate activity while solubility is primarily determined by the magnesium content of the solid. Bulk solubility is a composite that concurs with established values. The findings demonstrate the type of ACC that forms is tuned by Mg2+ and CO3-2- concentration and suggest ACC structure, not bulk composition, is a reliable indicator of intermediate phase. This chemical framework also provides a basis for interpreting apparent differences between observations of ACC in synthetic and natural systems that reconciles previous structural studies.

Mergelsberg, Sebastian T.↗

DOE OSTI2020

Fast GPU 3D diffeomorphic image registration

3D image registration is one of the most fundamental and computationally expensive operations in medical image analysis. Here, we present a mixed-precision, Gauss–Newton–Krylov solver for diffeomorphic registration of two images. Our work extends the publicly available CLAIRE library to GPU architectures. Despite the importance of image registration, only a few implementations of large deformation diffeomorphic registration packages support GPUs. Our contributions are new algorithms to significantly reduce the run time of the two main computational kernels in CLAIRE: calculation of derivatives and scattered-data interpolation. Additionally, we deploy (i) highly-optimized, mixed-precision GPU-kernels for the evaluation of scattered-data interpolation, (ii) replace Fast-Fourier-Transform (FFT)-based first-order derivatives with optimized 8th-order finite differences, and (iii) compare with state-of-the-art CPU and GPU implementations. As a highlight, we demonstrate that we can register clinical images in less than 6 s on a single NVIDIA Tesla V100. This amounts to over 20 speed-up over the current version of CLAIRE and over 30 speed-up over existing GPU implementations.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Numerical investigation of the role of free-stream turbulence in boundary-layer separation

The aerodynamic performance of lifting surfaces operating at low Reynolds number conditions is impaired by laminar separation. In most cases, transition to turbulence occurs in the separated shear layer as a result of a series of strong hydrodynamic instability mechanisms. Although the understanding of these mechanisms has been significantly advanced over the past decades, key questions remain unanswered about the influence of external factors such as free-stream turbulence (FST) and others on transition and separation. The present study is driven by the need for more accurate predictions of separation and transition phenomena in ‘real world’ applications, where elevated levels of FST can play a significant role (e.g. turbomachinery). Numerical investigations have become an integral part in the effort to enhance our understanding of the intricate interactions between separation and transition. Due to the development of advanced numerical methods and the increase in the performance of supercomputers with parallel architecture, it has become feasible for low Reynolds number application ( $O(10^{5})$ ) to carry out direct numerical simulations (DNS) such that all relevant spatial and temporal scales are resolved without the use of turbulence modelling. Because the employed high-order accurate DNS are characterized by very low levels of background noise, they lend themselves to transition research where the amplification of small disturbances, sometimes even growing from numerical round-off, can be examined in great detail. When comparing results from DNS and experiment, however, it is beneficial, if not necessary, to increase the background disturbance levels in the DNS to levels that are typical for the experiment. For the current work, a numerical model that emulates a realistic free-stream turbulent environment was adapted and implemented into an existing Navier–Stokes code based on a vorticity–velocity formulation. The role FST plays in the transition process was then investigated for a laminar separation bubble forming on a flat plate. FST was shown to cause the formation of the well-known Klebanoff mode that is represented by streamwise-elongated streaks inside the boundary layer. Increasing the FST levels led to accelerated transition, a reduction in bubble size and better agreement with the experiments. Moreover, the stage of linear disturbance growth due to the inviscid shear-layer instability was found to not be ‘bypassed’.

Mechanics↗