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At least 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Performance of methods for SARS-CoV-2 variant detection and abundance estimation within mixed population samples

The accurate identification of SARS-CoV-2 (SC2) variants and estimation of their abundance in mixed population samples (e.g., air or wastewater) is imperative for successful surveillance of community level trends. Assessing the performance of SC2 variant composition estimators (VCEs) should improve our confidence in public health decision making. Here, we introduce a linear regression based VCE and compare its performance to four other VCEs: two re-purposed DNA sequence read classifiers (Kallisto and Kraken2), a maximum-likelihood based method (Lineage deComposition for Sars-Cov-2 pooled samples (LCS)), and a regression based method (Freyja). We simulated DNA sequence datasets of known variant composition from both Illumina and Oxford Nanopore Technologies (ONT) platforms and assessed the performance of each VCE. We also evaluated VCEs performance using publicly available empirical wastewater samples collected for SC2 surveillance efforts. Bioinformatic analyses were performed with a custom NextFlow workflow (C-WAP, CFSAN Wastewater Analysis Pipeline). Relative root mean squared error (RRMSE) was used as a measure of performance with respect to the known abundance and concordance correlation coefficient (CCC) was used to measure agreement between pairs of estimators. Based on our results from simulated data, Kallisto was the most accurate estimator as it had the lowest RRMSE, followed by Freyja. Kallisto and Freyja had the most similar predictions, reflected by the highest CCC metrics. We also found that accuracy was platform and amplicon panel dependent. For example, the accuracy of Freyja was significantly higher with Illumina data compared to ONT data; performance of Kallisto was best with ARTICv4. However, when analyzing empirical data there was poor agreement among methods and variations in the number of variants detected (e.g., Freyja ARTICv4 had a mean of 2.2 variants while Kallisto ARTICv4 had a mean of 10.1 variants). This work provides an understanding of the differences in performance of a number of VCEs and how accurate they are in capturing the relative abundance of SC2 variants within a mixed sample (e.g., wastewater). Such information should help officials gauge the confidence they can have in such data for informing public health decisions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Actinide Mixing Optimization Solver

The Actinide Mixing Optimization Solver (AMOS) is a set of programs written in MATLAB that computes theoretical mixes of different uranium, plutonium, thorium, and other actinide materials given a list of isotopic reference materials. Constraints are applied depending on the desired product and a mixture is computed to meet the specified requirements. The optimal mixture consists of a product that uses the lowest possible number of initial actinide materials and has the lowest cost. AMOS is currently applied to particular reference material requests from the sponsoring agency (NNSA) on behalf of the IAEA.

Baldwin, Aaron Taylor↗
DOE OSTI2021

Rapid Charging Made Practical in Graphite-Based Lithium Batteries: Surface-Acoustic Wave Turbulent Electrolyte Mixing to Overcome Diffusion Limited Charging Rates

One of the key limits in rapidly recharging a lithium-ion battery is the depletion of lithium ions within the electrolyte adjacent the anode during charging and long diffusion time to overcome this depletion. It also causes dendrite formation, inefficient use of the lithium, and battery degradation over many charge-discharge cycles. Because the liquid electrolyte remains quiescent and unmixed, this depletion layer's depth rapidly grows to match the anode-cathode separation distance at even modest charge rates. The solution proposed by PI Prof. James Friend and Co-PI Prof. Ping Liu, both from the University of California, San Diego, is to mix the electrolyte and minimize the Li ion concentration gradient during charging. Even in the presence of the separator, the charging rate could then be significantly increased. They propose to accomplish this using surface acoustic wave (SAW)-driven acoustic streaming, a technique employing 10-mW fingernail-sized solid-state devices from the telecommunications industry to drive turbulent mixing to submicron length scales in a manner completely compatible with the typical 20700 and 18650 cells used in electric vehicles.

25 ENERGY STORAGE↗
DOE OSTI2020

Determination of Mixed Gas Compressibility in Nuclear Fuel Rods

Gas behavior of mixed gas species becomes non-ideal at pressures above atmospheric. Theoretical calculations of the behavior can be calculation intensive and may diverge from actual values depending on the model used and its applicability to the range of interest. Experimental data is lacking in the literature for varied pressure compressibility factors (Z) for most pure gas systems and even more rare for mixed gas species. This work covers the experimental determination of compressibility factors for pure Ar and a 1:1 Xe:He gas mixture. The deviation from ideal at elevated pressures can lead to incorrect results when not accounted for during expansion experiments such as those used when characterizing the pressure in nuclear fuel rods.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

In-line mixing printhead for multimaterial aerosol jet printing

An aerosol jet printhead comprising an in-line static mixer can mix multiple aerosol streams for co-deposition from a single nozzle. A printhead was designed, fabricated, and tested, demonstrating in-plane functionally graded films. The inline mixing printhead can be used with a compact aerosol jet deposition system.

Secor, Ethan Benjamin↗
DOE OSTI2023

"Enabling Mixed Autonomy Traffic Control"

We demonstrate a new capability of automated vehicles: mixed autonomy traffic control. With this new capability, automated vehicles can shape the traffic flows composed of other non-automated vehicles, which has the promise to improve safety, efficiency, and energy outcomes in transportation systems at a societal scale. Investigating mixed autonomy mobile traffic control must be done in situ given that the complex dynamics of other drivers and their response to a team of automated vehicles cannot be effectively modeled. This capability has been blocked because there is no existing scalable and affordable platform for experimental control. This paper introduces an extensible open-source hardware and software platform, enabling a team of 100 vehicles to execute several different vehicular control algorithms as a collaborative fleet, composed of three different makes and models, which drove 22752 miles in a combined 1022 hours, over 5 days in Nashville, TN in November 2022.

Nice, Matthew↗
DOE OSTI2026

Methanol mixing−controlled compression ignition enabled via homogeneous charge compression ignition of dimethyl ether through catalytic decomposition of methanol

Methanol is a potentially attractive fuel for marine and off−road engines owing to its availability at bunkering and global distribution locations. Although methanol is well−distributed worldwide, its fuel chemistry and ignition properties make it poorly suited as a direct drop−in replacement for diesel fuel in compression−ignition engines. However, industrial processes are regularly used to convert methanol, via catalytic dehydration, to dimethyl ether (DME) over nonprecious metal catalysts. This chemical conversion can occur at relatively low pressures, temperatures, and catalyst space velocities, highlighting a potential opportunity to generate DME via onboard catalytic dehydration of methanol. DME’s fuel kinetic and ignition properties for compression ignition are much more favorable than those of methanol or even diesel fuel, but DME is more challenging than diesel fuel or methanol to pump, store, and deliver through conventional diesel fueling injection hardware. Thus, a potential opportunity exists to use the ignition and kinetic properties of DME, with the transportation and delivery advantages of methanol, in a methanol−fueled mixing−controlled compression−ignition engine. The present work explores performance, combustion behavior, and emissions reduction opportunities for methanol mixing−controlled combustion, enabled by a HCCI of DME that represents a small fraction of the total fuel energy that can be generated onboard via catalytic dehydration of methanol.

Splitter, Derek [ORNL] (ORCID:0000000174044047)↗
DOE OSTI2025

Higher levels of mixed-linkage (1,3;1,4)-β-glucan in transgenic grasses may impact soil C processing

Carbohydrates, including mixed-linkage glucan (MLG), in grass cell walls make them a valuable potential feedstock for biofuel production. Hence, the development of transgenic grasses with elevated levels of MLG is being actively pursued worldwide. Changes in chemical and physical root characteristics of MLG-overproducing transgenic plants can affect processing of the root-derived carbon (C) by soil microorganisms, impacting soil C cycling. Here, this study is the first attempt to elucidate the impact of MLG-related genetic modifications on root traits, root decomposition, and soil C processing. We explored four genotypes of Brachypodium ( Brachypodium distachyon ): a wildtype, a loss-of-function mutant with low MLG, an MLG overexpressing line, and a line lacking MLG hydrolase (with high MLG), incubating their roots in soils of two contrasting vegetation histories: monoculture switchgrass and polyculture restored prairie. The four genotypes exhibited contrasting root MLG and soluble sugar concentrations, and different growth phenotypes. Roots with the highest MLG content resulted in a ∼55 % increase in microbial biomass C compared to wildtype in both soils. However, the genotype effects on C mineralization rates were influenced by the vegetation history, with significant effects observed only in the soil from switchgrass but not prairie origin. While further work is required to understand the full impact of MLG-overproducing plants on soil C accrual, our findings suggest that their influence on soil C processes cannot be discounted.

Brachypodium distachyon↗
DOE OSTI2024

Mapping TpPa-1 covalent organic framework (COF) molecular interactions in mixed solvents via atomistic modeling and experimental study

Complex solvent environments continue to limit the widespread adoption of organic solvent nanofiltration (OSN) in many chemical industry applications. In this paper we employ a commercially available covalent organic framework (COF), TpPa-1, and force field models to molecularly map separation performance of TpPa-1 membrane in mixed solvents. To minimize time and length scale mismatch between atomistic modeling and experiments, solvent permeance was normalized with water in modeling and experimental results to enable direct comparison. Model outputs, such as organic solvent permeance and solute rejection rate, matched well with filtration results. Since the atomistic models assume that all mass transfer is via through-pore transport, the discrepancies between modeling and experimental results provide insights on the effect of linear polymer defects, adsorption and interstitial mass transfer on polycrystalline COF membrane performance. In sum, force field models can serve as digital twins of COF membranes to simulate separation processes while capturing the effects of COF structure, chemistry, and crystallinity on membrane performance in complex organic solvent environments. Finally, this approach will provide insight into future COF design and synthesis for persisting separation challenges.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Photoinduced Halide Segregation in Ruddlesden–Popper 2D Mixed Halide Perovskite Films

2D lead halide perovskites, which exhibit bandgap tunability and increased chemical stability, have been found to be useful for designing optoelectronic devices. Reducing dimensionality with decreasing number of layers (n = 10–1) also imparts resistance to light-induced ion migration as seen from the halide ion segregation and dark recovery in mixed halide (Br:I = 50:50) perovskite films. The light-induced halide ion segregation efficiency, as determined from difference absorbance spectra, decreases from 20% to <1% as the dimensionality is decreased for 2D perovskite film from n = 10 to 1. The segregation rate constant (ksegregation), which decreases from 5.9 × 10 –3 s –1 (n = 10) to 3.6 × 10 –4 s –1 (n = 1), correlates well with nearly an order of magnitude decrease observed in charge-carrier lifetime (τ average = 233 ps for n = 10 vs τ avg = 27 ps for n = 1). The tightly bound excitons in 2D perovskites make charge separation less probable, which in turn decreases the halide mobility and resulting phase segregation. Furthermore, the importance of controlling the dimensionality of the 2D architecture in suppressing halide ion mobility is discussed.

14 SOLAR ENERGY↗
DOE OSTI2022

Tuning Surface Acidity of Mixed Conducting Electrodes: Recovery of Si‐Induced Degradation of Oxygen Exchange Rate and Area Specific Resistance

Abstract Metal oxides are an important class of functional materials, and for many applications, ranging from solid oxide fuel/electrolysis cells, oxygen permeation membranes, and oxygen storage materials to gas sensors (semiconducting and electrolytic) and catalysts, the interaction between the surface and oxygen in the gas phase is central. Ubiquitous Si‐impurities are known to impede this interaction, commonly attributed to the formation of glassy blocking layers on the surface. Here, the surface oxygen exchange coefficient ( k chem ) is examined for Pr 0.1 Ce 0.9 O 2‐δ (PCO), a model mixed ionic electronic conductor, via electrical conductivity relaxation measurements, and the area‐specific resistance (ASR) by electrochemical impedance spectroscopy. It is demonstrated that even low silica levels, introduced by infiltration, depress k chem by a factor 4000, while the ASR increases 40‐fold and we attribute this to its acidity relative to that of PCO. The ability to fully regenerate the poisoned surface by the subsequent addition of basic Ca‐ or Li‐species is further shown. This ability to not only recover Si‐poisoned surfaces by tuning the relative surface acidity of an oxide surface, but subsequently outperform the pre‐poisoned response, promises to extend the operating life of materials and devices for which the catalytic oxygen/solid interface reaction is central.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

New Chemical Dopant and Counterion Mechanism for Organic Electrochemical Transistors and Organic Mixed Ionic–Electronic Conductors

Abstract Organic mixed ionic–electronic conductors (OMIECs) have varied performance requirements across a diverse application space. Chemically doping the OMIEC can be a simple, low‐cost approach for adapting performance metrics. However, complex challenges, such as identifying new dopant materials and elucidating design rules, inhibit its realization. Here, these challenges are approached by introducing a new n‐dopant, tetrabutylammonium hydroxide (TBA‐OH), and identifying a new design consideration underpinning its success. TBA‐OH behaves as both a chemical n‐dopant and morphology additive in donor acceptor co‐polymer naphthodithiophene diimide‐based polymer, which serves as an electron transporting material in organic electrochemical transistors (OECTs). The combined effects enhance OECT transconductance, charge carrier mobility, and volumetric capacitance, representative of the key metrics underpinning all OMIEC applications. Additionally, when the TBA + counterion adopts an “edge‐on” location relative to the polymer backbone, Coulombic interaction between the counterion and polaron is reduced, and polaron delocalization increases. This is the first time such mechanisms are identified in doped‐OECTs and doped‐OMIECs. The work herein therefore takes the first steps toward developing the design guidelines needed to realize chemical doping as a generic strategy for tailoring performance metrics in OECTs and OMIECs.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Mixed Ionic–Electronic Conductor of Perovskite Li x La y MO 3-δ toward Carbon-Free Cathode for Reversible Lithium–Air Batteries

Mixed ionic–electronic conductors (MIECs) can play a pivotal role in achieving high energies and power densities in rechargeable batteries owing to their ability to simultaneously conduct ions and electrons. In our study, a new strategy is proposed wherein late 3d transition metals (TMs) are substituted into a perovskite Li-ion conductor to transform it into a Li-containing MIEC. First-principles calculations show that perovskite Li x La y MO 3 with late 3d TMs have a low oxygen vacancy formation energy, implying high electron carrier concentrations corresponding to high electronic conductivity. The activation barriers for Li diffusion in Li x La y MO 3 (M = Ti, Cr, Mn, Fe, and Co) are below 0.411 eV, resulting in high Li-ion conductivity. The designed perovskites of Li0.34La 0.55 MnO 3-δ experimentally prove to have high electronic (2.04 × 10 -3 S cm -1 ) and Li-ion (8.53 × 10 -5 S cm -1 ) conductivities, and when applied in a carbon-free cathode of a Li–air cell, they deliver superior reversibility at 0.21 mAh cm -2 over 100 charge/discharge cycles while avoiding the degradation associated with carbonaceous materials. Finally, this strategy enables the effective design of Li-conducting MIEC and reversible Li–air batteries.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Rapid Access to Diverse Multicomponent Hierarchical Nanostructures from Mixed–Graft Block Copolymers

Multicomponent nanostructured materials assembled from molecular building blocks received wide attention due to their precisely integrated multifunctionalities. However, discovery of these materials with desirable composition and morphology was limited by their low synthetic scalability and narrow structural tuning window with given building blocks. Here, we report a scalable and diversity-oriented synthetic approach to hierarchically structured nanomaterials based on a few readily accessible building blocks. Mixed-graft block copolymers containing sequence-defined side chains were prepared through ring-opening metathesis copolymerization of three or four types of macromonomers. Intramolecularly defined interfaces promoted the formation of ordered hierarchical structures with lattice sizes tunable across multiple length scales. Finally, the same set of macromonomers were arranged and combined in different ways, providing access to diverse morphologies in the resultant structures.

36 MATERIALS SCIENCE↗
DOE OSTI2022

State elimination for mixed‐integer optimal control of partial differential equations by semigroup theory

Abstract Mixed‐integer optimal control problems governed by partial differential equations (MIPDECOs) are powerful modeling tools but also challenging in terms of theory and computation. We propose a highly efficient state elimination approach for MIPDECOs that are governed by partial differential equations that have the structure of an abstract ordinary differential equation in function space. This allows us to avoid repeated calculations of the states for all time steps, and our approach is applied only once before starting the optimization. The presentation of theoretical results is complemented by numerical experiments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A solution framework for linear PDE-constrained mixed-integer problems

Abstract We present a general numerical solution method for control problems with state variables defined by a linear PDE over a finite set of binary or continuous control variables. We show empirically that a naive approach that applies a numerical discretization scheme to the PDEs to derive constraints for a mixed-integer linear program (MILP) leads to systems that are too large to be solved with state-of-the-art solvers for MILPs, especially if we desire an accurate approximation of the state variables. Our framework comprises two techniques to mitigate the rise of computation times with increasing discretization level: First, the linear system is solved for a basis of the control space in a preprocessing step. Second, certain constraints are just imposed on demand via the IBM ILOG CPLEX feature of a lazy constraint callback. These techniques are compared with an approach where the relations obtained by the discretization of the continuous constraints are directly included in the MILP. We demonstrate our approach on two examples: modeling of the spread of wildfire and the mitigation of water contamination. In both examples the computational results demonstrate that the solution time is significantly reduced by our methods. In particular, the dependence of the computation time on the size of the spatial discretization of the PDE is significantly reduced.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

McCormick envelopes in mixed-integer PDE-constrained optimization

McCormick envelopes are a standard tool for deriving convex relaxations of optimization problems that involve polynomial terms. Such McCormick relaxations provide lower bounds, for example, in branch-and-bound procedures for mixed-integer nonlinear programs but have not gained much attention in PDE-constrained optimization so far. This lack of attention may be due to the distributed nature of such problems, which on the one hand leads to infinitely many linear constraints (generally state constraints that may be difficult to handle) in addition to the state equation for a pointwise formulation of the McCormick envelopes and renders bound-tightening procedures that successively improve the resulting convex relaxations computationally intractable. We analyze McCormick envelopes for a model problem class that is governed by a semilinear PDE involving a bilinearity and integrality constraints. We approximate the nonlinearity and in turn the McCormick envelopes by averaging the involved terms over the cells of a partition of the computational domain on which the PDE is defined. This yields convex relaxations that underestimate the original problem up to an a priori error estimate that depends on the mesh size of the discretization. These approximate McCormick relaxations can be improved by means of an optimization-based bound-tightening procedure. We show that their minimizers converge to minimizers to a limit problem with a pointwise formulation of the McCormick envelopes when driving the mesh size to zero. We provide a computational example, for which we certify all of our imposed assumptions. The results point to both the potential of the methodology and the gaps in the research that need to be closed. Our methodology provides a framework first for obtaining pointwise underestimators for nonconvexities and second for approximating them with finitely many linear inequalities in an infinite-dimensional setting.

Approximations and Expansions↗
DOE OSTI2025

A mixed-integer PDE-constrained optimization formulation for constructing electromagnetic cloaks with multiple materials

We study the design of an electromagnetic cloak from multiple materials with an additional constraint on the mass of the cloak. Our problem is an example of a topology optimization problem, and we formulate this problem as a mixed-integer partial-differential equation constrained optimization (MIPDECO) problem, where Maxwell’s equation models the propagation of the wave through the cloak and surrounding medium. We use binary variables to model the assignment of the different materials, and their relevant properties (permittivity and density). The mass constraint adds a nontrivial constraint to this problem. We propose a two-phase strategy to solve this problem. In the first phase, we solve a continuous relaxation, and then propose a new variant of the feasibility pump that exploits the structure of the PDE to obtain an initial integral solution candidate. In the second phase, we use a trust-region approach to improve this incumbent. We also consider a continuation or mesh-sequencing approach to find better solutions faster on consecutively finer meshes. We present detailed numerical results to illustrate the effectiveness of our approaches for constructing multi-material cloaks with a mass constraint.

Calculus of Variations and Optimization↗