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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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At least 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Calculation of Dynamical Response Functions Using a Bound-State Method

Abstract We investigate a method to extract response functions (dynamical polarisabilities) directly from a bound-state approach applied to calculations of perturbation-induced reactions. The use of a square-integrable basis leads to a response in the form of a sum of $$\delta $$ δ functions. We integrate this over energy and fit a smooth function to the resulting stepwise-continuous one. Its derivative gives the final approximation to the physical response function. We show that the method reproduces analytical results where known, and analyse the details for a variety of models. We apply it to some simple models, using the stochastic variational method as the numerical method. Albeit we find that this approach, and other numerical techniques, have some difficulties with the threshold behavior in coupled-channel problems with multiple thresholds, its stochastic nature allows us to extract robust results even for such cases.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Field-Deployable Quantum Memory for Quantum Networking

High-performance quantum memories are an essential component for regulating temporal events in quantum networks. As a component in quantum-repeaters, they have the potential to support the distribution of entanglement beyond the physical limitations of fiber loss. This will enable key applications such as quantum key distribution, network-enhanced quantum sensing, and distributed quantum computing. Here, we present a quantum memory engineered to meet real-world deployment and scaling challenges. The memory technology utilizes a warm rubidium vapor as the storage medium, and operates at room temperature, without the need for vacuum- and/or cryogenic- support. Here, we demonstrate performance specifications of high-fidelity retrieval (95%) and low operation error (10 –2 ) at a storage time of 160 µs for single-photon level quantum memory operations. We further show a substantially improved storage time (with classical-level light) of up to 1ms by suppressing atomic diffusions. The device is housed in an enclosure with a standard 2U rackmount form factor, and can robustly operate on a day scale in a noisy environment. This result marks an important step toward implementing quantum networks in the field.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Operation and Control of Electric Vehicle Charger with Enhanced Dynamic Performance Under Non-Ideal Grid Voltage Condition

This paper presents a three-phase electric vehicle charger connected to the grid, featuring multiple boost converters on the DC side, specifically designed to ensure smooth, oscillation-free power transfer during unsymmetrical voltage sags. Precise control mechanisms are implemented on the boost converter side to regulate both voltage and current on the electric vehicle side, thereby maintaining optimal charging conditions. The control architecture for both the grid-connected and boost converter components is based on the Lyapunov energy function, which is employed to achieve superior dynamic performance and stability. The system's robustness and reliability are demonstrated through its ability to maintain stable operation and efficient power transfer despite fluctuations in grid conditions. Furthermore, the implementation of Lyapunov-based control ensures rapid response and minimal energy loss, enhancing the overall efficiency of the system. To validate the effectiveness of this approach, a comprehensive model of the system was developed and tested using MATLAB/Simulink, with detailed computer simulations conducted across various significant case studies.

DC-DC boost converter↗
DOE OSTI2025

Rolling Behavior of Surface Tagged Aluminum 6061 using Photoluminescent Oxides

Physical tagging of nuclear fuel is potentially one way of tracking throughout the fuel lifecycle. The process of tagging can take many forms, but one promising method is to embed a small amount of photoluminescent particles in the surface of a material which are not detectable under normal illumination but are readily visible under excitation by ultraviolet light. The goal of this project was to explore the potential to tag simulated nuclear fuel cladding with small ceramic particles, via laser beam welding or gas tungsten arc welding, and measure the photoluminescent response. Surface tagging using this method has demonstrated viability and detectability throughout this project; work in FY24 focused on the survivability of these tags through subsequent deformation processing similar to what taggants in a fuel manufacturing environment would be subjected to. This work demonstrated that particles are readily visible in the as-welded state (i.e., before subsequent rolling treatment to represent mechanical processing of a fuel material), but visibility is reduced as the deformation is induced. Despite the reduction in photoluminescence, the taggants are still visible after rolling processes are performed, making this surface tagging technique a promising candidate for nuclear fuel cladding tagging. This work demonstrated, though, that targeted optimization work would be necessary to develop a robust taggant depending on the fidelity and luminescent properties required.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Identifying Decoherence Mechanisms in Superconducting Qubits through Advanced Materials Characterization

Although superconducting qubits have emerged as a leading technology platform for quantum computing through large improvements in device coherence times and gate fidelity in recent years, the presence of defects and impurities at the interfaces and surfaces in the constituent materials continue to limit performance and serve as a critical barrier in achieving scalable quantum systems. Understanding and eliminating these sources of quantum decoherence in superconducting qubit devices requires dedicated studies aimed at establishing robust structure-property relationships that will enable researchers to target and eliminate defects strategically. As part of the Superconducting Materials and Systems (SQMS) center, we have extensively employed state-of-the-art materials characterization techniques, including scanning/transmission electron microscopy, secondary ion mass spectrometry, atom probe tomography, x-ray diffraction, and x-ray photoelectron spectroscopy in conjunction with device measurements to elucidate such relationships. In this talk, I will discuss some of our recent findings, including linking atomic defects to microwave loss in surface oxides, linking impurities in the Josephson Junction to qubit parameters, and linking low temperature precipitates to device performance. By applying these insights, we have been able to strategically develop and implement mitigation strategies for reliable fabrication of high coherence superconducting qubits.

Murthy, A. [Fermilab] (ORCID:0000000176776866)↗
DOE OSTI2026

Identifying Decoherence Mechanisms in Superconducting Qubits through Advanced Materials Characterization

Although superconducting qubits have emerged as a leading technology platform for quantum computing through large improvements in device coherence times and gate fidelity in recent years, the presence of defects and impurities at the interfaces and surfaces in the constituent materials continue to limit performance and serve as a critical barrier in achieving scalable quantum systems. Understanding and eliminating these sources of quantum decoherence in superconducting qubit devices requires dedicated studies aimed at establishing robust structure-property relationships that will enable researchers to target and eliminate defects strategically. As part of the Superconducting Materials and Systems (SQMS) center, we have extensively employed state-of-the-art materials characterization techniques, including scanning/transmission electron microscopy, secondary ion mass spectrometry, atom probe tomography, x-ray diffraction, and x-ray photoelectron spectroscopy in conjunction with device measurements to elucidate such relationships. In this talk, I will discuss some of our recent findings, including linking atomic defects to microwave loss in surface oxides, linking impurities in the Josephson Junction to qubit parameters, and linking low temperature precipitates to device performance. By applying these insights, we have been able to strategically develop and implement mitigation strategies for reliable fabrication of high coherence superconducting qubits.

Murthy, A. [Fermilab] (ORCID:0000000176776866)↗
DOE OSTI2026

Multi-Objective design of interlocking metasurfaces using conditional diffusion models

Unit cell design remains a major challenge for interlocking metasurfaces, a promising joining technology for dissimilar materials, due to the complex, competing, multivariate design space and the need for rapid adaptation to varying performance requirements. This study explores Conditional Diffusion Models as a design optimization tool for interlocking metasurfaces. Given the complex, competing, multivariate design space for interlocking metasurfaces, unit cell design remains a major challenge for this joining technology. We trained a conditional diffusion model on 25,000 finite element analysis-simulated interlocking metasurface unit cells to generate designs with tailored thermo-mechanical properties (tensile strength, shear strength, and thermal conductivity) based on specified performance criteria. The model demonstrated a success rate of approximately 72 % in producing designs that met specified property bounds. The conditional diffusion model generated both thermally resistive and conductive designs, revealing clear trends in design characteristics: taller, dendritic structures were advantageous for tensile loads, while shorter, robust designs excelled in shear applications. Our findings indicate that the model's performance is more influenced by the breadth of the design space than by the quantity of training data, highlighting the importance of expansive design domains for generating innovative solutions. This work establishes conditional diffusion models as a highly efficient and adaptable tool for rapid interlocking metasurface unit cell design, paving the way for advancements in multi-material joining technologies, as well as highlighting the justification to leverage conditional diffusion models as design tools across complex design domains.

Conditional diffusion models↗
DOE OSTI2025

Harnessing peptide–cellulose interactions to tailor the performance of self-assembled, injectable hydrogels

Taking inspiration from natural systems, such as spider silk and mollusk nacre, that employ hierarchical assembly to attain robust material performance, we leveraged matrix–filler interactions within reinforced polymer–peptide hybrids to create self-assembled hydrogels with enhanced properties. Specifically, cellulose nanocrystals (CNCs) were incorporated into peptide–polyurea (PPU) hybrid matrices to tailor key hydrogel features through matrix–filler interactions. Herein, we examined the impact of peptide repeat length and CNC loading on hydrogelation, morphology, mechanics, and thermal behavior of PPU/CNC composite hydrogels. The addition of CNCs into PPU hydrogels resulted in increased gel stiffness; however, the extent of reinforcement of the nanocomposite gels upon nanofiller inclusion also was driven by PPU architecture. Temperature-promoted stiffening transitions observed in nanocomposite PPU hydrogels were dictated by peptide segment length. Analysis of the peptide secondary structure confirmed shifts in the conformation of peptidic domains (α-helices or β-sheets) upon CNC loading. Finally, PPU/CNC hydrogels were probed for their injectability characteristics, demonstrating that nanofiller–matrix interactions were shown to aid rapid network reformation (∼10 s) upon cessation of high shear forces. Overall, this research showcases the potential of modulating matrix–filler interactions within PPU/CNC hydrogels through strategic system design, enabling the tuning of functional hydrogel characteristics for diverse applications.

42 ENGINEERING↗
DOE OSTI2022

Self-assembly of cocontinuous nanostructured copolymer templates with compositional and architectural dispersity. Final Report

Cocontinuous nanostructured materials in which multiple domains of different materials simultaneously span three dimensional space offer opportunities to achieve combined properties not possible with a single homogeneous material. These architectures have importance in a broad range of energy-relevant technologies including batteries, supercapacitors, fuel cells, separation membranes, and catalysts. Achieving such structures in polymeric materials has been of long-standing interest in the field, due to both the inherently attractive properties of cocontinuous polymer morphologies as well as their ability to serve as templates for other functional nanostructured materials. Our work on this project has established that randomly-linked polymer architectures constructed from two immiscible polymer strands provide robust and highly tunable approaches to disordered cocontinuous nanostructures. In particular, we developed a detailed understanding of how the parameters (linker functionality and strand length, asymmetry, and dispersity) of randomly-linked networks controlled the breadth of the cocontinuous window over which both phases remain percolated. We further characterized how these nanostructures undergo orientation, while retaining cocontinuity, under mechanical deformation. We also compared their behavior to that of random multi-block polymers of linear architecture, which show similar propensity to form disordered nanostructures, albeit over narrower ranges of parameter space. Finally, we have explored the development of functional polymer nanostructures and composites based in part on the fundamental understanding obtained via this project.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Scaling from Flux Towers to Ecosystem Models: Regional Constraints on Carbon Cycle Processes from Atmospheric Carbonyl Sulfide (Final Report)

DOE supported research suggests that gross primary productivity (GPP) is largely underestimated by global earth system models [Welp et al., 2011], reflecting the persistent challenge in extrapolating from local-scale GPP observations to global-scale earth system models. This poor understanding of GPP at large spatial scales is of particular concern in tropical forests. In tropical forests, some earth systems models forecast a powerful feedback between a warming climate and a decline in GPP resulting in forest dieback. While this simulated feedback is intensely debated, we lack robust large-scale constraints on GPP that are needed to resolve this debate. In particular, carbon dioxide measurements provide valuable information on net carbon flux, but not on the gross flux associated with GPP. Here we conducted a study of regional-to-global scale GPP using atmospheric carbonyl sulfide to provide a new constraint on GPP mechanisms in earth system models. Our project activities integrated modeling, in situ measurement, and remote sensing techniques to resolve GPP for the Amazon as well as global scale trends. The results of this work included initiating airborne carbonyl sulfide monitoring in the Amazon, training for postdocs and graduate students at a Hispanic Serving Institution, fundamental advances in carbonyl sulfide budgets [e.g. Hilton et al., Nature Climate Change, 2017], and high-profile publications that focused on GPP trends for the Amazon [Stinecipher et al., GRL, 2022] and global historical GPP trends [Campbell, et al., Nature, 2017]. Based on the suggestion of our DOE program manager, we published a state-of-the-science commentary to the scientific community on GPP monitoring with COS [Campbell et al., EOS, 2017] which was selected as the cover story. DOE support was acknowledged in all reports. The importance of this research to understanding climate change was communicated to the general public through community seminars (Rotary, Public Libraries, State Parks), an op-ed (SF Chronicle), and interviews in the mass media including two stories in the New York Times (4/5/17; 7/30/18), one of which was especially widely read after it was featured in the New York Time’s Quote of the Day.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Multiphysics Modeling of Microreactors with NEAMS codes, and Validation Based on KRUSTY Reactivity Insertion

The NEAMS Multiphysics Applications team continues to assess code usability and functionality for microreactor design and safety analyses, while demonstrating that NEAMS tools capture both steady-state and transient behavior across distinct microreactor concepts. In FY2025, the team advanced full-core, high-fidelity, multiphysics models that solve more complex problems and strengthen verification/validation for several microreactor systems: heat-pipe microreactor (HPMR), gas-cooled microreactor (GCMR), and the KRUSTY experiment. These models employ the MOOSE MultiApp/Transfers architecture with Griffin for neutronics, BISON for heat conduction/thermomechanics, Sockeye for heat pipes, SAM/THM for coolant channels and loops, and SWIFT for hydride behavior, with meshes generated via the MOOSE Reactor Module. The graphite models available in the Grizzly code were also investigated for future analyses. For the HPMR, a Na-HPMR variant was constructed to align with recently validated heat-pipe experiments and Sockeye’s LCVF capability, enabling mechanistic heat-pipe transients and startup modeling. The Na-HPMR will serve as the primary model for HPMR investigations in upcoming tasks. The load-following and single heat-pipe failure scenarios (Griffin/BISON/Sockeye), which were previously modeled for the K-HPMR, were replicated for the Na-HPMR, showing strong negative temperature feedback and highly localized thermal effects, respectively, while the startup case captured vapor-front progression and heat-removal activation. Solid mechanics was added to the previously built K-HPMR full-core model in BISON, showing minimal impact on steady-state reactivity yet enabling stress-field predictions that prepare the path for full-core TRISO performance analyses. For the GCMR, automated steady-state and four transient scenarios were executed using Griffin/BISON/SAM/SWIFT. Results confirm robust inherent safety: power collapses promptly in loss-of-cooling events, the inlet-temperature drop settles to a new equilibrium, and a single-channel blockage yields only a ~30 K local fuel-temperature rise with <0.4% power decrease. SWIFT-predicted hydrogen redistribution affects reactivity during both steady-state and transient conditions, underscoring its importance. A Brayton-cycle balance of plant (BOP) model in SAM/THM demonstrated stable startup behavior, and xenon-driven reactivity during load following was analyzed. To improve TRISO-compact temperature fidelity, a fast multiscale Heat Source Decomposition (HSD) treatment was implemented. Against heterogeneous benchmarks, HSD reduces underprediction of kernel temperatures and lowers predicted peak powers in reactivity-insertion transients compared to previous homogenized models. KRUSTY warm-critical validation progressed from FY2024 baselines: the 15Ȼ insertion shows excellent agreement in peak power (~2% high) and temperature trends, and the 30Ȼ case was automated via a feedback controller that maintained power near 3 kW for ~150 s with close agreement to data. The successful modeling of the warm critical tests has laid a strong foundation for simulating more complex nuclear system tests in the years ahead. Throughout FY2025, developer feedback was provided (e.g., MOOSE batch mesh generation, distributed pre-split meshes, Griffin sweeper on displaced meshes), several new models were contributed to the Virtual Test Bed, and an OECD-NEA WPRS multiphysics benchmark based on the HPMR was initiated to enable broader cross-comparison and best-practice development with the nuclear community at large.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Development of an ERT‐Based Framework for Bentonite Buffers Monitoring From Laboratory Tests: 1. Characterizing Thermal–Hydrological–Mechanical Processes

Abstract Bentonite clay is widely used in engineered barrier systems for the permanent disposal of high‐level radioactive waste due to its low permeability, high swelling capacity, and thermal stability. However, the complex thermal‐hydrological‐mechanical (THM) processes induced by heating from decaying radioactive waste and hydration from surrounding rock can lead to heterogeneous changes that are difficult to measure and predict. This study develops an Electrical Resistivity Tomography (ERT)‐based framework for monitoring THM processes, progressing from sample‐scale to bench‐scale tests, to inform field‐scale applications. Sample‐scale tests analyzed small bentonite samples under controlled variations in water content, temperature, and porosity to establish fundamental resistivity relationships. Bench‐scale tests involved larger bentonite columns subjected to heating (up to 200°C) and hydration under controlled pressure, simulating repository conditions. ERT measurements, complemented by X‐ray CT imaging, temperature monitoring, and tracing sensors, revealed coupled THM processes, such as hydration‐induced compression, swelling, and thermal gradients, leading to complex resistivity patterns. The results demonstrate the potential of ERT for capturing THM‐induced resistivity changes, though challenges remain in upscaling and quantitative analysis. This study evaluates laboratory test capabilities and proposes future improvements for understanding THM‐induced resistivity responses. A conceptual framework for ERT implementation in field‐scale monitoring is presented, synthesizing findings from both scales and exploring how ERT data can inform long‐term modeling and reduce prediction uncertainties. Overall, this ERT‐based framework offers a robust method for monitoring bentonite buffers, aiding in early issue detection and supporting the safe long‐term disposal of radioactive waste in geological repositories, while highlighting the need for future development. Plain Language Summary Bentonite clay is crucial in engineered barrier systems (EBS) for containing high‐level radioactive waste due to its ability to absorb water, swell, seal and remain stable under high temperatures. When bentonite absorbs water and heats up from radioactive decay, it experiences complex changes in its physical and mechanical properties. Understanding these changes is important for ensuring the long‐term safety and effectiveness of EBS. This study used Electrical Resistivity Tomography (ERT), a non‐invasive method that measures electrical conductivity to monitor these changes during laboratory experiments. The ERT data revealed significant variations in resistivity corresponding to changes in water content, temperature, and density, providing detailed spatial and temporal insights into the behavior of bentonite. These findings enhance our ability to predict the long‐term performance of bentonite barriers, ensuring the safe containment of radioactive waste. By improving our understanding of bentonite's behavior, this research supports the development of more reliable and effective barrier systems for radioactive waste disposal, protecting the environment and public health. Key Points ERT monitoring was employed to capture resistivity changes in bentonite during controlled heating and hydration experiments, providing insights into THM processes ERT data reveal significant resistivity changes correlated with water content, temperature, and mechanical effects, enhancing the understanding of THM dynamics in bentonite This study explores the potential of the framework for application in field‐scale EBS monitoring, emphasizing the need for integrating additional geophysical methods for comprehensive subsurface imaging

Chen, Hang↗
DOE OSTI2022

Two-dimensional shaping of Solov'ev equilibrium with vacuum using external coils

In this work, we demonstrate a method for constructing the Solov'ev equilibrium with any given 2D shape surrounded by a vacuum region using external poloidal field coils, based on the method previously developed by T. Xu and R. Fitzpatrick [Nuclear Fusion, 59, 064002 (2019)]. The computational domain consists of two parts: the plasma region, where the solution is the same as the Solov'ev solution, and the vacuum region, where the magnetic field generated by external coils as well as plasma current is determined using the Green function method through a matching condition near the separatrix. However, the method is not limited to the Solov'ev equilibrium in particular. In conclusion, the accuracy, efficiency, and robustness of such a scheme suggest that this method may be applied to the 2D shaping of a tokamak plasma with a vacuum region using external coils in general.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Rapid cooling of the in-plane motion of two-dimensional ion crystals in a Penning trap to millikelvin temperatures

Here, we propose a highly feasible technique with no experimental overhead to rapidly cool the in-plane degrees of freedom of large two-dimensional ion crystals in Penning traps. Through simulations, we demonstrate that our approach enables the in-plane modes to cool down to a temperature of around 1 mK in less than 10 ms. Our technique relies on near-resonant coupling of the poorly cooled in-plane motions and the efficiently cooled out-of-plane motions, and is achieved without introducing additional potentials. The rapid cooling enabled by our approach is in contrast to typical operating conditions, where our simulations of the laser cooling dynamics suggest that the ion crystal's in-plane motion cools very slowly on a timescale of several hundreds of milliseconds, a rate likely slower than experimental heating rates. Our work sets the stage for sub-Doppler laser cooling of the planar motion, and more robust and versatile quantum simulation and quantum sensing experiments with two-dimensional crystals in Penning traps.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Transverse energy–energy correlations of jets in the electron–proton deep inelastic scattering at HERA

We study the event shape variables, transverse energy–energy correlation TEEC (cosφ) and its asymmetry ATEEC (cosφ) in deep inelastic scattering (DIS) at the electron–proton collider HERA, where φ is the angle between two jets defined using a transverse-momentum (k T ) jet algorithm. At HERA, jets are defined in the Breit frame, and the leading nontrivial transverse energy–energy correlations arise from the 3-jet configurations. With the help of the NLOJET++, these functions are calculated in the leading order (LO) and the next-to-leading order (NLO) approximations in QCD at the electron–proton center-of-mass energy $\sqrt{s}$ = 314 GeV. We restrict the angular region to -0.8 ≤ cosφ ≤ 0.8, as the forward- and backward-angular regions require resummed logarithmic corrections, which we have neglected in this work. Following experimental jet-analysis at HERA, we restrict the DIS-variables x, y = Q 2 /(xs), where Q 2 = -q 2 is the negative of the momentum transfer squared q 2 , to 0 ≤ x ≤ 1, 0.2 ≤ y ≤ 0.6, and the pseudo-rapidity variable in the laboratory frame (η lab ) to the range -1 ≤ η lab ≤ 2.5. The TEEC and ATEEC functions are worked out for two ranges in Q 2 , defined by 5.5GeV 2 ≤ Q 2 ≤ 80GeV 2 , called the low-Q 2 -range, and 150GeV 2 ≤ Q 2 ≤ 1000GeV 2 , called the high-Q 2 -range. We show the sensitivity of these functions on the parton distribution functions (PDFs), the factorization (μ F ) and renormalization (μ R ) scales, and on α s (M$^2_Z$). Of these the correlations are stable against varying the scale μ F and the PDFs, but they do depend on μ R . For the choice of the scale μ R =$\sqrt{\langle ET \rangle^2+Q^2}$, advocated in earlier jet analysis at HERA, the shape variables TEEC and ATEEC are found perturbatively robust. These studies are useful in the analysis of the HERA data, including the determination of α s (M$^2_Z$) from the shape variables.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

A sharp interface Lagrangian-Eulerian method for flexible-body fluid-structure interaction

This paper introduces a sharp-interface approach to simulating fluid-structure interaction (FSI) involving flexible bodies described by general nonlinear material models and across a broad range of mass density ratios. This new flexible-body immersed Lagrangian-Eulerian (ILE) scheme extends our prior work on integrating partitioned and immersed approaches to rigid-body FSI. Our numerical approach incorporates the geometrical and domain solution flexibility of the immersed boundary (IB) method with an accuracy comparable to body-fitted approaches that sharply resolve flows and stresses up to the fluid-structure interface. Unlike many IB methods, our ILE formulation uses distinct momentum equations for the fluid and solid subregions with a Dirichlet-Neumann coupling strategy that connects fluid and solid subproblems through simple interface conditions. As in earlier work, we use approximate Lagrange multiplier forces to treat the kinematic interface conditions along the fluid-structure interface. This penalty approach simplifies the linear solvers needed by our formulation by introducing two representations of the fluid-structure interface, one that moves with the fluid and another that moves with the structure, that are connected by stiff springs. This approach also enables the use of multi-rate time stepping, which allows us to use different time step sizes for the fluid and structure subproblems. Our fluid solver relies on an immersed interface method (IIM) for discrete surfaces to impose stress jump conditions along complex interfaces while enabling the use of fast structured-grid solvers for the incompressible Navier-Stokes equations. The dynamics of the volumetric structural mesh are determined using a standard finite element approach to large-deformation nonlinear elasticity via a nearly incompressible solid mechanics formulation. This formulation also readily accommodates compressible structures with a constant total volume, and it can handle fully compressible solid structures for cases in which at least part of the solid boundary does not contact the incompressible fluid. Selected grid convergence studies demonstrate second-order convergence in volume conservation and in the pointwise discrepancies between corresponding positions of the two interface representations as well as between first and second-order convergence in the structural displacements. The time stepping scheme is also demonstrated to yield second-order convergence. To assess and validate the robustness and accuracy of the new algorithm, comparisons are made with computational and experimental FSI benchmarks. Test cases include both smooth and sharp geometries in various flow conditions. Furthermore, we also demonstrate the capabilities of this methodology by applying it to model the transport and capture of a geometrically realistic, deformable blood clot in an inferior vena cava filter.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Experimental and kinetic modeling study of the low- temperature and high-pressure combustion chemistry of straight chain pentanol isomers: 1-, 2- and 3-Pentanol

Pentanols have received significant attention as a potential alternative fuel or fuel additive owing to their high energy densities and low vapor pressure. The development of robust chemical kinetic models for alternative fuels which can provide accurate and efficient predictions of combustion performance across a wide range of engine relevant conditions is important in developing cleaner, more efficient combustors. Although the high temperature oxidation kinetics of pentanol isomers has been researched considerably, their low temperature combustion chemistry needs further investigation. While previously proposed low temperature mechanisms for 1-pentanol based on analogy and rate rules need further refinement, the low temperature oxidation kinetics of 2-pentanol and 3-pentanol has not been studied previously by any means, experimentally or theoretically. A newly developed kinetic mechanism is presented in this work for the three straight chain pentanol isomers: 1-, 2- and 3-pentanol. Low temperature kinetics is based on a recent study by Lockwood et al., 2022 [20] involving theoretical calculations at the CCSD(T)/cc-pV∞Z level of theory for the oxidation pathways involving alcohol peroxy radicals. Rate of production analyses performed in this study highlight the importance of the newly added pressure-dependent reactions of the α-alcohol peroxy radical forming an RO 2 adduct. While the α-alcohol fuel radical reacts with O 2 to directly decompose via a chemically activated pathway at low pressures, the formation of the RO 2 adduct is favored at high pressures. Furthermore, the detailed model is comprehensively validated against new ignition experiments at low temperature and high pressure, together with the wide range of data available in the literature. Both qualitative and quantitative predictions of the experimental data using the proposed kinetic model are satisfactory for all three pentanol isomers studied here.

1-pentanol↗
DOE OSTI2026

Oxidation, Oligomerization, Isomerization of Hydrocarbons Using Metal–Organic Frameworks

The selective conversion of hydrocarbons into higher-value fuels and feedstocks is essential to the global energy and chemistry landscape. While porous inorganic materials have enabled significant progress in these transformations, achieving high activity, selectivity, and stability under industrially relevant conditions remains challenging. Metal–organic frameworks (MOFs) are a promising platform to precisely control active-site environments and interrogate structure–function relationships due to their crystallinity, tunability, and porosity. This review highlights relevant hydrocarbon transformations and outlines the general mechanisms for oxidation, oligomerization, and isomerization. Metal node acidity, confinement effects, and active site dispersion are analyzed for their impact on reactivity and selectivity across the three reactions. Lastly, we discuss current limitations in catalyst stability and offer a perspective on integrating reticular chemistry with high-throughput experimentation and machine learning to accelerate the discovery and design of robust, next-generation MOF catalysts.

Catalysts↗