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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DOE OSTI2022

Sol-gel processing of a covalent organic framework for the generation of hierarchically porous monolithic adsorbents

Covalent organic frameworks (COFs) have emerged as a versatile material platform for such applications as chemical separations, chemical reaction engineering, and energy storage. Their inherently low mechanical stability, however, frequently renders existing methods of pelletization ineffective, contributing to pore collapse, pore blockage, or insufficient densification of crystallites. Here, we present a process for the shaping and densifying of COFs into robust centimeter-scale porous monoliths without the need for templates, additives, or binders. This process minimizes mechanical damage from shear-induced plastic deformation and further provides a network of interparticle mesopores that we exploit in accessing analyte capacities above those achievable from the intrinsic COF structure. Using a lattice-gas model, we accurately capture the monolithic structure across the mesoporous range and tie pore architecture to performance in both gas-storage and -separation applications. Collectively, these results represent a substantial step in the practical applicability of COFs and other mechanically weak porous materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

A pseudo-two-dimensional (P2D) model for FeS 2 conversion cathode batteries

Conversion cathode materials are gaining interest for secondary batteries due to their high theoretical energy and power density. However, practical application as a secondary battery material is currently limited by practical issues such as poor cyclability. To better understand these materials, we have, for this study, developed a pseudo-two-dimensional model for conversion cathodes. We apply this model to FeS 2 – a material that undergoes intercalation followed by conversion during discharge. The model is derived from the half-cell Doyle–Fuller–Newman model with additional loss terms added to reflect the converted shell resistance as the reaction progresses. We also account for polydisperse active material particles by incorporating a variable active surface area and effective particle radius. Using the model, we show that the leading loss mechanisms for FeS 2 are associated with solid-state diffusion and electrical transport limitations through the converted shell material. The polydisperse simulations are also compared to a monodisperse system, and we show that polydispersity has very little effect on the intercalation behavior yet leads to capacity loss during the conversion reaction. Finally, we provide the code as an open-source Python Battery Mathematical Modeling (PyBaMM) model that can be used to identify performance limitations for other conversion cathode materials.

25 ENERGY STORAGE↗

DOE OSTI2023

Storm Surge Modeling as an Application of Local Time-Stepping in MPAS-Ocean

This paper presents the first practical application of local time-stepping (LTS) schemes in the Model for Prediction Across Scales-Ocean (MPAS-O). We use LTS schemes in a single-layer, global ocean model that predicts the storm surge around the eastern coast of the United States during Hurricane Sandy. The variable-resolution meshes used are of unprecedentedly high resolution in MPAS-O, containing cells as small as 125 m wide in Delaware Bay. It is shown that a particular, third-order LTS scheme (LTS3) produces sea-surface height solutions that are of comparable quality to solutions produced by the classical four-stage, fourth-order Runge-Kutta method (RK4) with a uniform time step on the same meshes. Furthermore, LTS3 is up to 35% faster in the best cases considered, where the number of cells using the coarse time-step relative to those using the fine time-step is as low as 1:1. This shows that LTS schemes are viable for use in MPAS-O with the added benefit of substantially less computational cost. The results of these performance experiments inform us of the requirements for efficient mesh design and configuration of LTS regions for LTS schemes. In particular, we see that for LTS to be efficient on a given mesh, it is important to have enough cells using the coarse time-step relative to those using the fine time-step, typically at least 1:5 to see an increase in performance.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

High Energy Density Shape Memory Polymers Using Strain-Induced Supramolecular Nanostructures

Shape memory polymers are promising materials in many emerging applications due to their large extensibility and excellent shape recovery. However, practical application of these polymers is limited by their poor energy densities (up to ~1 MJ/m 3 ). Here, we report an approach to achieve a high energy density, one-way shape memory polymer based on the formation of strain-induced supramolecular nanostructures. As polymer chains align during strain, strong directional dynamic bonds form, creating stable supramolecular nanostructures and trapping stretched chains in a highly elongated state. Upon heating, the dynamic bonds break, and stretched chains contract to their initial disordered state. This mechanism stores large amounts of entropic energy (as high as 19.6 MJ/m 3 or 17.9 J/g), almost six times higher than the best previously reported shape memory polymers while maintaining near 100% shape recovery and fixity. The reported phenomenon of strain-induced supramolecular structures offers a new approach toward achieving high energy density shape memory polymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Optimizing dicyandiamide pretreatment conditions for enhanced structure and electronic properties of polymeric graphitic carbon nitride

Graphitic carbon nitride, a polymeric semiconductor, possesses a distinctive electronic band structure and exceptional chemical stability, making it a highly promising material for various catalytic applications such as electrocatalysis, photocatalysis, and photo-electrocatalysis. However, its practical applications remain limited due to its low active site density and poor electrical conductivity. In this study, to overcome such limitations, we have conducted a thorough investigation to explore the impact of dicyandiamide (DCDA) precursor pretreatment prior to thermal polymerization to graphitic carbon nitride. The DCDA precursor was subjected to various pretreatment methods including grinding using mortar and pestle, recrystallization through stirring or probe sonication after dissolving in deionized water, and freeze drying, prior to thermal polymerization at 550 °C for 2 hours. The structural and morphological properties of the catalysts prepared were compared and characterized by X-ray diffraction (XRD), attenuated total reflectance–Fourier transform infrared (ATR-IR) spectroscopy, scanning electron microscopy (SEM), transmission electron microscopy (TEM), and X-ray photoelectron spectroscopy (XPS) analysis while the electronic band gap properties were determined based on density functional theory (DFT) calculations for a set of crystalline systems having C/N ratios similar to those identified experimentally. In comparison to direct thermal polymerization, pretreated samples rendered the same product yield, diverse morphologies with flat or wrinkle structures, and reduced electrochemical resistance, making them suitable for use in various catalytic processes.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Fundamentals of bio-electrochemical sensing

The utilization of bio-functionalities such as biorecognition or catalysis derived them their name biosensors. Bio-electrochemical sensing is a new discipline that combines the advantages of biological detection and electrochemical transduction. Bio-electrochemical sensors are devices that use biological materials such as enzymes, antibodies, DNA, or cells as receptors to detect target analytes in a variety of samples. Electrodes convert biological interactions into electrical impulses, which can be studied using various electrochemical techniques. Bio-electrochemical sensors have demonstrated significant promise for use in clinical diagnostics, environmental monitoring, food safety, and biotechnology. Biosensors have received numerous applications in recent years because they are fast, simple, and inexpensive for practical applications. In this article, we cover the basic principles, design strategies, immobilization and regeneration techniques, along with the advantages and applications of bio-electrochemical sensors. Finally, this article discusses the rationale for developing electrochemical biosensors in the context of the various bio-receptors that can be applied.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Penetration of foliar-applied Zn and its impact on apple plant nutrition status: in vivo evaluation by synchrotron-based X-ray fluorescence microscopy

The absorption of foliar fertilizer is a complex process and is poorly understood. The ability to visualize and quantify the pathway that elements take following their application to leaf surfaces is critical for understanding the science and for practical applications of foliar fertilizers. By the use of synchrotron-based X-ray fluorescence to analyze the in vivo localization of elements, our study aimed to investigate the penetration of foliar-applied Zn absorbed by apple leaves with different physiological surface properties, as well as the possible interactions between foliar Zn level and the mineral nutrient status of treated leaves. The results indicate that the absorption of foliar-applied Zn was largely dependent on plant leaf surface characteristics. High-resolution elemental maps revealed that the high binding capacity of the cell wall for Zn contributed to the observed limitation of Zn penetration across epidermal cells. Trichome density and stomatal aperture had opposite effects on Zn fertilizer penetration: a relatively high density of trichomes increased the hydrophobicity of leaves, whereas the presence of stomata facilitated foliar Zn penetration. Low levels of Zn promoted the accumulation of other mineral elements in treated leaves, and the complexation of Zn with phytic acid potentially occurred owing to exposure to high-Zn conditions. The present study provides direct visual evidence for the Zn penetration process across the leaf surface, which is important for the development of strategies for Zn biofortification in crop species.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

A generalized platform for artificial intelligence-powered autonomous enzyme engineering

Proteins are the molecular machines of life with numerous applications in energy, health, and sustainability. However, engineering proteins with desired functions for practical applications remains slow, expensive, and specialist-dependent. Here we report a generally applicable platform for autonomous enzyme engineering that integrates machine learning and large language models with biofoundry automation to eliminate the need for human intervention, judgement, and domain expertise. Requiring only an input protein sequence and a quantifiable way to measure fitness, this automated platform can be applied to engineer a wide array of proteins. As a proof of concept, we engineer Arabidopsis thaliana halide methyltransferase (AtHMT) for a 90-fold improvement in substrate preference and 16-fold improvement in ethyltransferase activity, along with developing a Yersinia mollaretii phytase (YmPhytase) variant with 26-fold improvement in activity at neutral pH. This is accomplished in four rounds over 4 weeks, while requiring construction and characterization of fewer than 500 variants for each enzyme. This platform for autonomous experimentation paves the way for rapid advancements across diverse industries, from medicine and biotechnology to renewable energy and sustainable chemistry.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Overview of FLORIS updates

In this paper, we review updates made to the FLORIS (FLOw Redirection and Induction in Steady State) open-source framework for wind farm control modeling, design and analysis. The updates are focused on improvements for large arrays of turbines - including heterogenous inflows and incorporating second-order wake steering effects - design, and analysis tools for practical application of wind farm control, and improvements to the software architecture for best practices in modularization and cooperative development.

17 WIND ENERGY↗

DOE OSTI2022

Hidden variable in the electrocaloric effect of ferroics

Caloric effects allow for temperature control through adiabatic application of external fields and are actively explored for solid-state refrigeration. The common wisdom is that the application of ultrahigh fields enhances the effects, thus providing a route to their practical applications. Here, using the ferroelectric relaxor (Ba, Ca)(Ti, Zr)O 3 , we demonstrate that in ferroics, which are the prime candidates for such application, this is not true in general and that caloric effects can be enhanced through the reduction of the applied field. The explanation of such a counterintuitive response is in the dependence of the electrocaloric effect on the effective poling field that can be regarded as a “hidden” variable of the caloric effects.

36 MATERIALS SCIENCE↗

DOE OSTI2022

High-performance and stable AgSbTe 2 -based thermoelectric materials for near room temperature applications

AgSbTe 2 -based ternary chalcogenides show excellent thermoelectric performance at low- and middle-temperature ranges, yet their practical applications are greatly limited by their intrinsic poor thermodynamic stability. In this work, we demonstrate that AgSbTe 2 -based ternary chalcogenides can be stabilized for service below their decomposition threshold. A series of Ag x Sb 2-x Te 3-x (x = 1.0, 0.9, 0.8 and 0.7) samples have been prepared by the melt-quenching method. Among them, phase pure Ag 0.9 Sb 1.1 Te 2.1 is verified by comprehensive structural characterizations from macroscale by X-ray diffraction to microscale by energy-dispersive spectroscopy and then to sub-nanometer scale by atom probe tomography. This composition is further chosen for the stability investigation. The decomposition threshold of Ag 0.9 Sb 1.1 Te 2.1 appears around 473K. Below this temperature, the chemical compositions and thermoelectric properties are barely changed even after 720 h annealing at 473 K. The figure-of-merit (zT) value of Ag 0.9 Sb 1.1 Te 2.1 below the decomposition threshold is very competitive for real applications even compared with Bi 2 Te 3 -based alloys. The average zT of Ag 0.9 Sb 1.1 Te 2.1 at 300–473 K reaches 0.84, which is higher than most other thermoelectric materials in a similar temperature range, promising applications in miniaturized refrigeration and power generation near room temperature.

36 MATERIALS SCIENCE↗

DOE OSTI2023

UniKP: a unified framework for the prediction of enzyme kinetic parameters

Prediction of enzyme kinetic parameters is essential for designing and optimizing enzymes for various biotechnological and industrial applications, but the limited performance of current prediction tools on diverse tasks hinders their practical applications. Here, we introduce UniKP, a unified framework based on pretrained language models for the prediction of enzyme kinetic parameters, including enzyme turnover number (k cat ), Michaelis constant (K m ), and catalytic efficiency (k cat / K m ), from protein sequences and substrate structures. A two-layer framework derived from UniKP (EF-UniKP) has also been proposed to allow robust k cat prediction in considering environmental factors, including pH and temperature. In addition, four representative re-weighting methods are systematically explored to successfully reduce the prediction error in high-value prediction tasks. We have demonstrated the application of UniKP and EF-UniKP in several enzyme discovery and directed evolution tasks, leading to the identification of new enzymes and enzyme mutants with higher activity. UniKP is a valuable tool for deciphering the mechanisms of enzyme kinetics and enables novel insights into enzyme engineering and their industrial applications.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Reactive Flows in Porous Media: Challenges in Theoretical and Numerical Methods

We review theoretical and computational research, primarily from the past 10 years, addressing the flow of reactive fluids in porous media. The focus is on systems where chemical reactions at the solid–fluid interface cause dissolution of the surrounding porous matrix, creating nonlinear feedback mechanisms that can often lead to greatly enhanced permeability. Here, we discuss insights into the evolution of geological forms that can be inferred from these feedback mechanisms, as well as some geotechnical applications such as enhanced oil recovery, hydraulic fracturing, and carbon sequestration. Until recently, most practical applications of reactive transport have been based on Darcy-scale modeling, where averaged equations for the flow and reactant transport are solved. We summarize the successes and limitations of volume averaging, which leads to Darcy-scale equations, as an introduction to pore-scale modeling. Pore-scale modeling is computationally intensive but offers new insights as well as tests of averaging theories and pore-network models. We include recent research devoted to validation of pore-scale simulations, particularly the use of visual observations from microfluidic experiments.

wormhole formation↗

DOE OSTI2023

Report for the ASCR Workshop on Basic Research Needs in Quantum Computing and Networking - 2023

Employing quantum mechanical resources in computing and networking opens the door to new computation and communication models and potential disruptive advantages over classical counterparts. However, quantifying and realizing such advantages face extensive scientific and engineering challenges. Investments by the Department of Energy (DOE) have driven progress toward addressing such challenges. Quantum algorithms have been recently developed, in some cases offering asymptotic exponential advantages in speed or accuracy, for fundamental scientific problems such as simulating physical systems, solving systems of linear equations, or solving differential equations. Empirical demonstrations on nascent quantum hardware suggest better performance than classical analogs on specialized computational tasks favorable to the quantum computing systems. However, demonstration of an end-to-end, substantial and rigorously quantifiable quantum performance advantage over classical analogs remains a grand challenge, especially for problems of practical value. The definition of requirements for quantum technologies to exhibit scalable, rigorous, and transformative performance advantages for practical applications also remains an outstanding open question, namely, what will be required to ultimately demonstrate practical quantum advantage?

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Report for the ASCR Workshop on Basic Research Needs in Quantum Computing and Networking - 2023

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Acceleration of heavy ions in inverse free electron laser

In conventional linear accelerators, the beam is accelerated with a synchronous harmonic of the radio frequency field where the electric field component is collinear with the beam direction. This approach requires the design of complex accelerating structures, especially for low-energy heavy ions. If the beam motion were sustainably coupled to transverse electromagnetic fields, this could significantly simplify the accelerating structure design, and even allow acceleration with free-space waves. However, despite the long history of the proposed concept for accelerating low-velocity ion beams, it has not found practical application, partially because of the complexity of the technical design. In this paper, we present a practical design approach for this undulator-based accelerator for low-energy heavy-ions, reminiscent of the inverse free electron laser operating principle, but in a different parameter space.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

A Survey on Privacy in Graph Neural Networks: Attacks, Preservation, and Applications

Graph Neural Networks (GNNs) have gained significant attention owing to their ability to handle graph-structured data and the improvement in practical applications. However, many of these models prioritize high utility performance, such as accuracy, with a lack of privacy consideration, which is a major concern in modern society where privacy attacks are rampant. To address this issue, researchers have started to develop privacy-preserving GNNs. Despite this progress, there is a lack of a comprehensive overview of the attacks and the techniques for preserving privacy in the graph domain. In this survey, we aim to address this gap by summarizing the attacks on graph data according to the targeted information, categorizing the privacy preservation techniques in GNNs, and reviewing the datasets and applications that could be used for analyzing/solving privacy issues in GNNs. We also outline potential directions for future research in order to build better privacy-preserving GNNs.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Nuclear Criticality Safety Margin and Handbook Data: Concepts and Applications [Slides]

At the end of this briefing, personnel should be able to: • Define concepts associated with criticality safety margin • Provide and understand practical applications that illustrate safety margin concepts • Describe how safety margin is addressed in criticality safety evaluations • Improve documentation and communication of safety margin • Connect these concepts to related statements in the ANS-8 Standards • Find numerous applications for handbook data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗