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At least 361 records · Page 20

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DOE OSTI2022

Prediction of local concentration fields in porous media with chemical reaction using a multi scale convolutional neural network

The study of solute transport in porous media is of interest in many chemical engineering systems. Some example applications include packed bed catalytic reactors, filtration devices, and batteries. The pore scale modeling of these systems is time consuming and may require large computing resources, for this reason computational fluid dynamics (CFD) simulations are not practical if a large number of simulations is required, like in multiscale modeling, where a model at a large scale calls for pore scale simulations. It has been shown that neural networks can be trained with a dataset of flow simulations and then predict fields orders of magnitude faster, and with less computational resources, in new domains. However, it is crucial to provide the neural network with an effective description of the domain and the undergoing operating conditions to be able to train models that generalize accurately in unseen samples. Therefore, research is needed to employ neural networks in new complex systems. The appropriate training of a network for predicting coupled flow and solute transport processes is an outstanding problem due to the complex interplay between geometry and operating conditions. In this work, we train a multi scale convolutional neural network (MSNet) with a diverse dataset of simulations of transport and chemical reaction in porous media to predict the local concentration fields in images of porous media. Our dataset contains a wide diversity of sphere pack arrangements under different operating conditions (Péclet and Reynolds numbers). Further, we train a robust model by employing different input descriptors that represent the medium and the different operating conditions of each system. Our trained model is able to provide nearly instantaneous predictions, compared to around twenty hours of the CFD workflow, with less than 3.5% error on new geometries and transport conditions. Thus the model could be easily integrated in a multiscale workflow where fast response is needed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Thousands of small, novel genes predicted in global phage genomes

Small genes (<150nucleotides) have been systematically overlooked in phage genomes. We employ a large scale comparative genomics approach to predict >40,000 small-gene families in 2.3 million phage genome contigs. We find that small genes in phage genomes are approximately 3-fold more prevalent than in host prokaryotic genomes. Our approach enriches for small genes that are translated in microbiomes, suggesting the small genes identified are coding. More than 9,000 families encode potentially secreted or transmembrane proteins, more than 5,000families encode predicted anti-CRISPR proteins, and more than500families encode predicted antimicrobial proteins. By combining homology and genomic-neighborhood analyses, we reveal substantial novelty and diversity within phage biology, including small phage genes found in multiple host phyla, small genes encoding proteins that play essential roles in host infection, and small genes that share genomic neighborhoods and whose encoded proteins may share related functions.

Fremin, Brayon↗

DOE OSTI2026

Catabolism of lignin-related methoxylated compounds in white-rot fungi utilizes non-canonical oxidoreductases

White-rot fungi (WRF) are the most effective lignin-degrading organisms in nature, making them essential to Earth’s carbon cycle. Lignin is a highly methoxylated, heterogeneous biopolymer derived from plants. However, the pathways WRF use to metabolize methoxylated aromatic monomericcompounds as carbon sources remain unidentified. Here, we employ a systems biology approach to elucidate the intracellular catabolism of vanillate – a monomethoxylated aromatic compound – in two white-rot fungi (WRF), Gelatoporia subvermispora and Trametes versicolor. We identified and biochemically validated a four-enzyme pathway that converts vanillate into ß-ketoadipate – a metabolite that enters central carbon metabolism. This pathway deviates from typical bacterial pathways, where vanillate is initially demethylated and ring-cleaved by intradiol dioxygenases; instead, oxidative decarboxylation occurs prior to ring cleavage by extradiol dioxygenases. Thus, we conducted an in-depth investigation of ring cleavage and further downstream catabolism by the identified fungal enzymes using biochemical and structural approaches. This revealed non-canonical enzymes, including a highly substrate-specific extradiol dioxygenase and a metal-free, promiscuous reductase, the latter capable of acting on catabolic intermediates derived from both methoxylated and non-methoxylated aromatic compounds. This work emphasizes the potential of WRF and their enzymes to advance lignin valorization and enhance our understanding of their role during wood decay.

dioxygenase↗

DOE OSTI2020

Refining internal bilayer structure of bicelles resolved by extended-q small angle X-ray scattering

The internal profile across the bilayer reveals important structural information regarding the crystallinity of acyl chains or the positions of encapsulated species. Here, we demonstrate that a simple five-layer-core-shell discoidal model can be employed tobest fit the extended-qsmall angle X-ray scattering (SAXS) data and resolvethe bilayer internal structure (with sub-nanometer resolution) of a nanoscale discoidal system comprised of a mixture of long-and short-chain lipids(known as “bicelles”). In contrast to the traditional core-shell discoidal model, the detailed structure in the hydrophobic core such as the methylene and methyl groups can be distinguished via this model. The refined model is validated by the SAXS data of bicelles whose electron scattering length density of the hydrophobic core is adjusted by the addition of a long-chain lipid with a fluorine-end group.The higher resolution of the bilayer internal structure can be employed to advance our understanding of the interaction and conformation of the membrane and associated molecules, such as membrane-associated proteins and locations of entrapped species in the lipid nanoparticles.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Silver-mediated separations: A comprehensive review on advancements of argentation chromatography, facilitated transport membranes, and solid-phase extraction techniques and their applications

The use of silver(I) ions in chemical separations, also known as argentation separations, is a powerful approach for the selective separation and analysis of many natural and synthetic organic compounds. In this review, a comprehensive discussion of the most common argentation separation techniques, including argentation-liquid chromatography (Ag-LC), argentation-gas chromatography (Ag-GC), argentation-facilitated transport membranes (Ag-FTMs), and argentation-solid phase extraction (Ag-SPE) is provided. For each of these techniques, notable advancements, optimized separations, and innovative applications are discussed. The review begins with an explanation of the fundamental chemistry underlying argentation separations, mainly the reversible π-complexation between silver(I) ions and carbon-carbon double bonds. Within Ag-LC, the use of silver(I) ions in thin-layer chromatography, high-performance liquid chromatography, as well as preparative LC are explored. This discussion focuses on how silver(I) ions are employed in the stationary and mobile phase to separate unsaturated compounds. For Ag-GC and Ag-FTMs, different silver compounds and supporting media are discussed, often with relation to olefin-paraffin separations. Ag-SPE has been widely employed for the selective extraction of unsaturated compounds from complex matrices in sample preparation. This comprehensive review of Ag-LC, Ag-GC, Ag-FTMs, and Ag-SPE techniques emphasizes the immense potential of argentation separations in separations science and serves as a valuable resource for researchers seeking to learn, optimize, and utilize argentation separations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Molecular dynamics and continuum analyses of the electrokinetic zeta potential in nanostructured slit channels

This work presents a theoretical and numerical study of electrokinetic flow and the zeta potential for the case of slit channels with nanoscale surface features of dimensions comparable to the Debye length, by employing molecular dynamics simulations and continuum-level analyses. Additionally, a simple analytical model for considering the average effect of such surface features producing nanoscale roughness is proposed by employing matched asymptotic solutions for the charge density and fluid flow field, and matching conditions that satisfy electroneutrality and the Onsager reciprocal relation between the electroosmotic flow rate and streaming current. The proposed analytical model quantitatively accounts for results from molecular dynamics simulations that consider the presence of ion solvation shells and surface hydration layers. Our analysis indicates that a simultaneous knowledge of the electroosmotic and pressure-driven flow rate or streaming current can be instrumental to unambiguously determine the zeta potential in the presence of nanoscale surface features.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

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 OSTI2023

Reduced chemical kinetic model for CH 4 -air non-premixed flames including excited and charged species

Electric fields can impact small laminar flames by changing their shape and overall behavior by acting on charged species produced in combustion. However, no reduced chemical kinetic model has been developed considering both major species and minor species related to flame characterization and flame behavior in the presence of an electric field. Here, this study presents a reduced chemical kinetic model for methane-air combustion which includes minor excited species (CH*and OH*) and charged species (H 3 O + , HCO + , C 2 H 3 O + , CH 5 O + , O$_{2}^{–}$, OH – , e – , CO$_{3}^{–}$, CHO$_{2}^{–}$, O – , CHO$_{3}^{–}$). The results employing the reduced chemistry model have been validated for a two-dimensional flame geometry by comparison with (i) detailed chemistry simulation results for species location and peak values, and (ii) experimental CH* chemiluminescence location, considering the self-repulsion of charges yet without externally applied electric field to the flame. This reduced chemical kinetic model, with 45 species and 216 reactions, shows a computational demand one-third that of employing its equivalent detailed chemistry (83 species and 394 reactions). The reduction is modest but significant considering that high fidelity is needed to capture the behavior of the chemi-ion and chemiluminescent species. Future works will involve the use of this model for simulations predicting flame behavior with applied electric field (i.e., field strength ≠0 kV/cm).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

An experimental and chemical kinetic modeling study of 4-butoxyheptane combustion

Here, the combustion kinetics of a novel oxygenated bioblendstock for diesel, 4-butoxyheptane (4-BH), was investigated experimentally using a flow reactor and a heated, high-pressure shock tube. The flow reactor experiments employed oxygen as the oxidizer and helium as the diluent with oxidation conducted at atmospheric pressure and 10 bar for temperatures from 400 to 1000 K at 20-K intervals. The fuel, oxidizer, and diluent flow rates were varied at different temperatures to maintain a constant initial fuel mole fraction of 1000 ppm, with stoichiometric equivalence ratio, and a residence time of 2.0 s. The reacted gas was fed to two separate GC systems that could qualitatively and quantitatively detect product species. Additionally, real fuel-air ignition delay time (IDT) data were collected using a heated, high-pressure shock-tube facility. Fuel lean (φ = 0.5) and stoichiometric (φ = 1.0) mixtures were investigated at 10 atm as well as at 30 atm for the fuel lean case for temperatures between 847 and 1259 K. A detailed chemical kinetics mechanism was developed to model the product distribution from the flow reactor and IDTs from the shock tube. The proposed model was able to predict the double NTC behavior in flow reactor experiments reasonably well. Model predictions at low temperatures were observed to be highly sensitive to the rate constants of ketohydroperoxide (KHP) decomposition in the case of the OOH group in α position which were modeled based on existing literature studies on ethers. It was noted that in the absence of theoretical or experimental studies, the rate constants for KHP decomposition used in the literature were empirically set. Additional studies are required to address the gap in model prediction obtained in this study and to reduce the uncertainty in kinetics models for ether oxidation. Predicted product concentrations and IDTs showed some quantitative agreement with experimental data, but the overall reactivity of the IDTs is underpredicted. Additionally, significant deviation is observed for the IDT results at 10 atm for the stoichiometric case with minor deviations for the other cases. The reaction pathways to the missing products were then further analyzed theoretically through quantum-mechanical calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Electronic Structures and Magnetism of Zr-, Th-, and U-based Metal-Organic Frameworks (MOFs) by Density Functional Theory

Metal-organic frameworks (MOFs) have recently gained wide interest as candidate materials for nuclear waste immobilization. While the fundamental thermodynamic properties, such as the substitution energies determine the favorability of radionuclide sequestration by utilization of a MOF matrix, the studies of MOF electronic structure reveal the role of d-, and/or f-electrons on changes in physical properties of actinide-containing materials. We use density functional theory (DFT) calculations to investigate the electronic structures of Zr-, Th-, and U-MOFs, including their electronic band structures and, where appropriate, their magnetic properties. We employ various DFT methods including DFT+U, collinear spin-polarization, spin-orbit coupling, and different flavors of exchange-correlation functionals to assess the robustness to the specific exchange-correlation functional. Unlike the Zr-, and Th-MOFs, the U-MOF is found to be sensitive to electron localization and spin; hence we explore the magnetic structure of the U-MOF in further detail.

Metal-Organic Framework, MOF, Actinides, DFT↗

DOE OSTI2024

A finite difference informed random walker (FDiRW) solver for strongly inhomogeneous diffusion problems

In nature, many complex multi-physics coupling problems exhibit strong diffusivity inhomogeneity. For instance, in the context of radionuclide absorption by porous wasteform materials within a flowing waste stream, the difference of species’ diffusivity in solid and liquid phases spans by 3~8 orders of magnitude. To solve the diffusion equations with strongly inhomogeneous diffusivity, traditional discretization-based methods, such as the Finite Difference Method (FDM), require infinitesimally small time steps (<10 -10 ) as high spatial resolutions are employed in most microstructure evolution processes, leading to prohibitively high computational costs. Here, this work developed an integrated numerical approach (FDiRW: Finite Difference informed Random Walk) to tackle this challenge. The idea is that utilizing the Random Walk concept, the fast diffusion is modeled as a superposition of point source’s solution for a concentration distribution while FDM is used to obtain the point source’s solution at each node. A mesh-coarsening algorithm is developed to generate an exclusive coarse mesh for FDiRW approach to maximize its efficiency. The effectiveness of the coarse mesh-based FDiRW approach is validated by benchmarking Finite Difference solutions. Numerical results demonstrated that FDiRW achieves a remarkable 1000x computational efficiency improvement over FDM while preserving desired accuracy for a medium-sized model of 192 × 192 × 192 grids. Finally, as models scale up, a floating-point operations (PLOPs) analysis of the FDiRW algorithm reveals that its computational complexity grows quadratically in terms of the number of nodes employed in computation.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Parallel three-dimensional simulations of quasi-static elastoplastic solids

Hypo-elastoplasticity is a flexible framework for modeling the mechanics of many hard materials under small elastic deformation and large plastic deformation. Under typical loading rates, most laboratory tests of these materials happen in the quasi-static limit, but there are few existing numerical methods tailor-made for this physical regime. Here, we extend to three dimensions a recent projection method for simulating quasi-static hypo-elastoplastic materials. The method is based on a mathematical correspondence to the incompressible Navier–Stokes equations, where the projection method of Chorin (1968) is an established numerical technique. We develop and utilize a three-dimensional parallel geometric multigrid solver employed to solve a linear system for the quasi-static projection. Our method is tested through simulation of three-dimensional shear band nucleation and growth, a precursor to failure in many materials. As an example system, we employ a physical model of a bulk metallic glass based on the shear transformation zone theory, but the method can be applied to any elastoplasticity model. We consider several examples of three-dimensional shear banding, and examine shear band formation in physically realistic materials with heterogeneous initial conditions under both simple shear deformation and boundary conditions inspired by friction welding.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Soft and transferable pseudopotentials from multi-objective optimization

Ab initio pseudopotentials are a linchpin of modern molecular and condensed matter electronic structure calculations. In this work, we employ multi-objective optimization to maximize pseudopotential softness while maintaining high accuracy and transferability. To accomplish this, we develop a formulation in which softness and accuracy are simultaneously maximized, with accuracy determined by the ability to reproduce all-electron energy differences between Bravais lattice structures, whereupon the resulting Pareto frontier is scanned for the softest pseudopotential that provides the desired accuracy in established transferability tests. We employ an evolutionary algorithm to solve the multi-objective optimization problem and apply it to generate a comprehensive table of optimized norm-conserving Vanderbilt (ONCV) pseudopotentials (https://github.com/SPARC-X/SPMS-psps). Here, we show that the resulting table is softer than existing tables of comparable accuracy, while more accurate than tables of comparable softness. The potentials thus afford the possibility to speed up calculations in a broad range of applications areas while maintaining high accuracy.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

A pseudospectral implicit particle-in-cell method with exact energy and charge conservation

The standard particle-in-cell (PIC) method employs explicit finite-difference (FD) methods (e.g. the leap-frog scheme) for both spatial and temporal integrations. Here, we employ a pseudospectral method for solving the Poisson equation and a fully implicit time integration to achieve exact energy conservation. The advantage of a pseudospectral field solver is its spectral accuracy in solving field solutions. Earlier studies of implicit time integration of PIC FD equations can enforce exact energy exchange between field and particles, resulting in exact energy-conserving schemes. Here, we prove that the exact energy conservation property can be carried over to the pseudospectral scheme. Simultaneously, we provide a solution to ensure a pseudospectral charge continuity equation. We demonstrate the new scheme in a 2D electrostatic PIC code. In conclusion, theoretical results are confirmed via numerical examples.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Ensemble Monte Carlo calculations with five novel moves

We introduce five novel types of Monte Carlo (MC) moves that brings the number of moves of ensemble MC calculations from three to eight. So far such calculations have relied on affine invariant stretch moves that were originally introduced by Christen (2007), walk moves by Goodman and Weare (2010) and quadratic moves by Militzer (2023). Ensemble MC methods have been very popular because they harness information about the fitness landscape from a population of walkers rather than relying on expert knowledge. Here we modified the affine method and employed a simplex of points to set the stretch direction. We adopt the simplex concept to quadratic moves. We also generalize quadratic moves to arbitrary order. Finally, we introduce directed moves that employ the values of the probability density while all other types of moves rely solely on the location of the walkers. We apply all algorithms to the Rosenbrock density in 2 and 20 dimensions and to the ring potential in 12 and 24 dimensions. We evaluate their efficiency by comparing error bars, autocorrelation time, travel time, and the level of cohesion that measures whether any walkers were left behind. Our code is open source.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Geometry-aware framework for deep energy method: An application to structural mechanics with hyperelastic materials

Here, in this work, we introduce a novel physics-informed framework named the Geometry-Aware Deep Energy Method (GADEM) for solving structural mechanics problems on different geometries. As the weak form of the physical system equation (or the energy-based approach) has demonstrated clear advantages compared to the strong form for solving solid mechanics problems, GADEM employs the weak form and aims to infer the solution on multiple shapes of geometries. Integrating a geometry-aware framework into an energy-based method results in an effective physics-informed deep learning model in terms of accuracy and computational cost. Different ways to represent the geometric information and to encode the geometric latent vectors are investigated in this work. We introduce a loss function of GADEM which is minimized based on the potential energy of all considered geometries. An adaptive learning method is also employed for the sampling of collocation points to enhance the performance of GADEM. We present some applications of GADEM to solve solid mechanics problems, including a loading simulation of a toy tire involving contact mechanics and large deformation hyperelasticity. The numerical results of this work demonstrate the remarkable capability of GADEM to infer the solution on various and new shapes of geometries using only one trained model.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Controlling MoO 2 and MoO 3 phases in MoO x /CNTs nanocomposites and their application to anode materials for lithium-ion batteries and capacitors

Molybdenum oxides (MoO 2 and MoO 3 ) are attractive anode materials for Li- and Na- ion batteries. Although there have been extensive studies on them individually, systematic and comparative studies are still lacking. Here, we demonstrate a facile and straightforward synthesis method to control the phase and oxidation state in the MoO x /CNTs nanocomposites via hydrothermal reaction followed by heat-treatment. By changing the gas atmosphere during the annealing process, well-dispersed MoO 2 /CNTs and MoO 3 /CNTs nanocomposites are formed without altering their overall morphology. This strategy enables us to investigate the true structure-property correlation of MoO x /CNTs nanocomposites by comparing the structure and electrochemical properties of MoO 2 /CNTs and MoO 3 /CNTs. When tested as anode materials for lithium-ion batteries, both HT-MoO 2&3 /CNTs electrodes show much-improved cycling stability and rate performance compared to the rod-shaped bulk MoO 3 electrode. In situ Mo K-edge x-ray absorption spectroscopy (XAS) has been further employed to compare and elucidate Li + storage mechanisms of both electrodes. When employed to the negative electrode of a high-power lithium-ion capacitor (LIC), the LIC full-cell composed of HT-MoO 3 /CNTs negative and activated carbon positive electrodes demonstrates impressive energy and power densities (~ 90 Wh kg –1 with 2000 W kg –1 ) and excellent cycling stability (96.8 % capacity retention after 300 cycles), revealing the versatility of the MoO x /CNTs electrodes in energy applications.

25 ENERGY STORAGE↗

DOE OSTI2021

Building envelope anomaly characterization and simulation using drone time-lapse thermography

Defects in building envelopes deteriorate over time without being visible to the human eye, while significantly impacting energy performance due to unaccounted heat transfer. Defects can be characterized in the infrared (IR) spectrum. However, IR readings are typically recorded at singular points in time, when in several cases anomalies can only be revealed at specific times of the day, possibly in different seasons of the year. This paper presents a novel workflow for 3D envelope defect characterization and modeling using aerial time-lapse IR data collection using drones. A comprehensive envelope thermal profile is developed for a case study building employing the photogrammetry software Agisoft Photoscan, which generates temporal IR inspections of building skins using multiple thermography orthomosaics. Point-cloud data is then translated into a CAD model and thermal zones for whole Building Energy Modeling (BEM) using Honeybee as a frontend to EnergyPlus to showcase the potential of inclusion of detailed 4D data. Envelope contributions in this case study’s anomalies showed heat losses of 6447.6 kWh, and Energy Use Intensity (EUI) differences of ~2 kWh/m 2 /year from the baseline. Finally, why there is currently little translation of this work in BEM software is discussed, while identifying limitations and future research in the employment of time-lapse thermography using drones for more accurate building envelope inspection and modeling.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗