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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 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Simultaneous material, shape and topology optimization

Using three design fields we develop an optimization environment that can simultaneously optimize material, shape and topology. We use the implicit representation of the boundaries with level-set functions that define the shape and topology. Differentiable R-functions allow us to combine these shapes and topology descriptions with Boolean operations. Additionally, we incorporate design dependent-stiffness materials with another design field. Notably, this framework accommodates design dependent loads, has the ability to introduce holes, and ensures the satisfaction of optimality criteria. It builds upon the fictitious domain, ersatz material, material interpolation and level-set methods. Additionally, it also borrows from parameterized density-based topology optimization methods. Since analytical sensitivities can be computed, we use efficient nonlinear programming algorithms to update the design instead of the Hamilton–Jacobi’s scheme of level-set methods. We illustrate the features of our framework by designing a cantilever beam with octet truss microlattice, a dam with design-dependent loads, and a composite clevis plate.

42 ENGINEERING↗
DOE OSTI2021

A general solution for accelerating screw dislocations in arbitrary slip systems with reflection symmetry

Solutions to the differential equations of linear elasticity in the continuum limit in arbitrary crystal symmetry are known only for steady-state dislocations of arbitrary character, i.e. line defects moving at constant velocity. Troubled by singularities at certain ‘critical’ velocities (typically close to certain sound speeds), these dislocation fields are thought to be too idealized, and divergences are usually attributed to neglecting the finite size of the core and to the restriction to constant velocity. In the isotropic limit, accelerating pure screw and edge dislocations were studied some time ago. A generalization to anisotropic crystals has been attempted for pure screw and edge dislocations only for some special cases. This work aims to fill the gap of deriving a general anisotropic solution for pure screw dislocations applicable to slip systems featuring a reflection symmetry, a prerequisite to studying pure screw dislocations without mixing with edge dislocations. Finally, further generalizations to arbitrary mixed dislocations as well as regularizations of the dislocation core are beyond the scope of this paper and are left for future work.

42 ENGINEERING↗
DOE OSTI2026

Revealing key structures for reversible sulfur redox in amorphous polymeric sulfur

Amorphous polymeric sulfur cathodes, such as sulfurized polyacrylonitrile (SPAN), enable high-energy lithium-sulfur batteries without cobalt or nickel, leveraging abundant sulfur. However, the limited in situ understanding of their synthesis and electrochemistry has impeded targeted optimization. Here, in this study, we integrate operando high-energy total scattering with sulfur K-edge X-ray absorption spectroscopy to monitor SPAN's formation and cycling in real time. Our results show that S-C bond formation halts further fusion of cyclized polyacrylonitrile, fostering π-π stacking and a transition from long-chain to short-chain sulfur-critical for reversible sulfur redox. These features synergistically minimize polysulfide dissolution and charge-transfer resistance, enabling optimized SPAN to achieve high capacity retention over 1,000 cycles. Operando X-ray absorption spectroscopy reveals that residual protons drive thiol-thione tautomerism, with lithium replacement during the first discharge causing ~20% irreversible capacity loss. To enhance performance, minimizing -NH groups and expanding pyridine networks are key. These findings transform SPAN optimization from empirical tuning to mechanism‑guided engineering and point the way towards sulfur loadings and energy densities competitive with state‑of‑the‑art Li‑ion cathodes.

25 ENERGY STORAGE↗
DOE OSTI2021

Decoupling the metal insulator transition and crystal field effects of VO 2

VO 2 is a highly correlated electron system which has a metal-to-insulator transition (MIT) with a dramatic change of conductivity accompanied by a first-order structural phase transition (SPT) near room temperature. The origin of the MIT is still controversial and there is ongoing debate over whether an SPT induces the MIT and whether the T c can be engineered using artificial parameters. We examined the electrical and local structural properties of Cr- and Co-ion implanted VO 2 (Cr-VO 2 and Co-VO 2 ) films using temperature-dependent resistance and X-ray absorption fine structure (XAFS) measurements at the V K edge. The temperature-dependent electrical resistance measurements of both Cr-VO 2 and Co-VO 2 films showed sharp MIT features. The T c values of the Cr-VO 2 and Co-VO 2 films first decreased and then increased relative to that of pristine VO 2 as the ion flux was increased. The pre-edge peak of the V K edge from the Cr-VO 2 films with a Cr ion flux ≥ 10 13 ions/cm 2 showed no temperature-dependent behavior, implying no changes in the local density of states of V 3d t 2g and e g orbitals during MIT. Extended XAFS (EXAFS) revealed that implanted Cr and Co ions and their tracks caused a substantial amount of structural disorder and distortion at both vanadium and oxygen sites. The resistance and XAFS measurements revealed that VO 2 experiences a sharp MIT when the distance of V–V pairs undergoes an SPT without any transitions in either the VO 6 octahedrons or the V 3d t 2g and eg states. This indicates that the MIT of VO 2 occurs with no changes of the crystal fields.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Advanced antireflection for back-illuminated silicon photomultipliers to detect faint light

Silicon photomultipliers have attracted increasing attention for detecting low-density light in both scientific research and practical applications in recent years; yet the photon losses due to reflection on the light-sensitive planar silicon surface considerably limit its photon detection efficiency. Here we demonstrate an advanced light trapping feature by developing the multi-layer antireflection coatings and the textured silicon surface with upright random nano-micro pyramids, which significantly reduces the reflection of faint light in a wide spectrum, from ultraviolet to infrared. Integrating this advanced photon confinement feature into next-generation back-illuminated silicon photomultiplier would increase the photon detection efficiency with significantly lower reflection and much more active areas. This advanced design feature offers the back-illuminated silicon photomultiplier broader application opportunities exemplified in the emerging scenarios such as nuclear medical imaging, light detection and ranging for autonomous driving, detection of scintillation light in ionizing radiation, as well as high energy physics.

42 ENGINEERING↗
DOE OSTI2020

toughio v1.2.2

TOUGH is a widely used general purpose numerical simulator designed for fluid and heat flows of multiphase, multicomponent fluid mixtures in porous and fractured media, which has been applied to many real-world problems such as underground geological storage, geothermal reservoir engineering or nuclear waste disposal, to name a few. `toughio` is a lightweight, object-oriented and vectorized Python library that aims to provide user-friendly routines to facilitate pre- and post-processing of a TOUGH simulation. Although its primary target is the latest version TOUGH3, `toughio` can also be used to read/write TOUGH2 input/output files. Currently, to the best of our knowledge, only PyTOUGH offers an exhaustive number of features to carry out a complete TOUGH simulation using a scripting language. `toughio` and PyTOUGH share the same objectives, yet with different approaches and philosophies. On the one hand, a PyTOUGH mesh is represented as a MULGRAPH geometry where elements can be unstructured horizontally but only layered vertically. It also checks that the model parameters are valid to ensure that a TOUGH simulation runs smoothly. On the other hand, although it provides basic meshing features, `toughio` mostly relies on common third-party softwares (e.g. Abaqus, FLAC3D, Gmsh, LaGriT) to generate the mesh by importing and converting it to a TOUGH mesh, which also conveniently facilitates the coupling of TOUGH with any other simulator that also supports the same mesh formats. Besides, `toughio` is designed to be just a TOUGH input and output file reader/writer. It assumes that the user knows what he is doing and does not verify the validity of the model parameters (`toughio` does verify the functional arguments).

Luu, Keurfon↗
DOE OSTI2023

Demonstration of Pronghorn’s Subchannel Code Modeling of Liquid-Metal Reactors and Validation in Normal Operation Conditions and Blockage Scenarios

Pronghorn-SC is a subchannel code within the Multiphysics Object-Oriented Simulation Environment (MOOSE). Initially designed to simulate flows in water-cooled, square lattice, subchannel assemblies, Pronghorn-SC has been expanded to simulate liquid-metal-cooled flows in triangular lattices, hexagonal subchannel assemblies. For this purpose, the algorithm of Pronghorn-SC was adapted to solve the subchannel equations as they are applicable to a hexagonal wire-wrapped sodium-cooled fast reactor. Cheng–Todreas models for pressure drop and cross-flow models were adopted and a coolant heat conduction term was added. To solve these equations, an improved implicit algorithm was developed robust enough to deal with the numerical issues, associated with low flow and recirculation phenomena. To confirm the prediction capability of Pronghorn-SC, calculations and comparisons with available experimental data of 19- and 37-pin assemblies were performed, as well as other subchannel codes. Finally, a flow blockage modeling feature was added. This capability was validated for both water-cooled square sub-assemblies and sodium-cooled hexagonal sub-assemblies, using experimental data of partially and fully blocked cases.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

IDAES-PSE 2.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost, most environmentally sustainable solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications. IDAES-PSE 2.0.0 Release Highlights Removal of deprecated features from IDAES v1 Update to Pyomo v6.5 – this required a number of updates to support the new NL solver writer and to address some changes in Pyomo Creation of new testing suite for backward compatibility, model robustness and verification More general implementation of the Helmholtz EoS. This brings some new features like standard property diagrams, choice of mass or mole basis, and new state variable options Standardizing names in Heat Exchanger models (breaking change from v2.0.0a2): Control Volumes named hot_side and cold_side Ports names hot_side_inlet, hot_side_outlet, cold_side_inlet and cold_side_outlet Config Blocks names hot_side_config and cold_side_config Config arguments for user provided names for each side: hot_side_name and cold_side_name. Updating Keras surrogate tool to use v1.1 of OMLT New prototype API for model initialization (idaes.core.initialization) The new API uses "Model Initializer" objects instead of class methods, allowing for the definition of multiple initialization routines for a single model A number of common, model agnostic initialization routines have also been defined, including initialization from data, block-decomposition and a general hierarchical approach equivalent to the existing method for common unit models New metadata for thermophysical properties – valid_range This can be used to record the range of values over which a property value can be trusted, such as the range of experimental data used to regress parameters A number of new utility functions have been added to check for properties with values outside the valid range and to set bounds based on this metadata Updated construction of balance expressions in Control Volumes to remove unneeded terms In the past, unneeded terms were added as a constant 0 term, however they will now be dropped entirely from the expression This was necessary due to more strict unit checking in the new Pyomo solver writer which no longer ignores 0 terms Updates to metadata for thermophysical properties to better define known properties and units of measurement This results in more strict enforcement of standard naming for thermophysical and reaction properties Users can still define custom properties, but these must be done explicitly using the define_custom_properties() method instead of being implicitly created by add_property() Updated convergence tester utility tool to support definition of benchmark files (JSON format) and comparison of performance to benchmarks Set default iteration limit for IPOPT in IDAES config to 200 iterations Update scaling of example models to work with new Pyomo NL solver writer Improve testing of extensions and examples infrastructure to avoid need for downloading files Updated distillation column to centralize common functionality and remove a number of Pyomo warnings

IDAES↗
DOE OSTI2025

Programmable low-coherence wavefronts for enhanced localization

Engineering the properties of electromagnetic wavefronts has become essential to imaging, wireless security, sensing, and wireless communication. In particular, wavefronts that exhibit low spatial coherence can enable sensing functionalities with high accuracy and low latency. The typical use of such wavefronts cannot take advantage of these possibilities, as they require the ability to dynamically reconfigure the wavefront in a controllable and repeatable fashion, over a broad spectral bandwidth. Here, we propose a new approach for generating broadband reconfigurable wavefronts which not only exhibit low spatial coherence at a particular frequency, but are also decorrelated with the wavefronts simultaneously generated at other frequencies. We demonstrate that this frequency-domain decorrelation is a key feature that, in combination with dynamic reconfigurability, enables localization measurements with an order-of-magnitude improvement in accuracy compared to the state of the art.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The tRNA discriminator base defines the mutual orthogonality of two distinct pyrrolysyl-tRNA synthetase/tRNAPyl pairs in the same organism

Abstract Site-specific incorporation of distinct non-canonical amino acids into proteins via genetic code expansion requires mutually orthogonal aminoacyl-tRNA synthetase/tRNA pairs. Pyrrolysyl-tRNA synthetase (PylRS)/tRNAPyl pairs are ideal for genetic code expansion and have been extensively engineered for developing mutually orthogonal pairs. Here, we identify two novel wild-type PylRS/tRNAPyl pairs simultaneously present in the deep-rooted extremely halophilic euryarchaeal methanogen Candidatus Methanohalarchaeum thermophilum HMET1, and show that both pairs are functional in the model halophilic archaeon Haloferax volcanii. These pairs consist of two different PylRS enzymes and two distinct tRNAs with dissimilar discriminator bases. Surprisingly, these two PylRS/tRNAPyl pairs display mutual orthogonality enabled by two unique features, the A73 discriminator base of tRNAPyl2 and a shorter motif 2 loop in PylRS2. In vivo translation experiments show that tRNAPyl2 charging by PylRS2 is defined by the enzyme's shortened motif 2 loop. Finally, we demonstrate that the two HMET1 PylRS/tRNAPyl pairs can simultaneously decode UAG and UAA codons for incorporation of two distinct noncanonical amino acids into protein. This example of a single base change in a tRNA leading to additional coding capacity suggests that the growth of the genetic code is not yet limited by the number of identity elements fitting into the tRNA structure.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Spin polarization engineering in 𝑑-wave altermagnets

Altermagnets host unconventional spin-polarized bands despite zero net magnetization, but controlling their spin structure remains challenging. Here, we theoretically propose a multifield approach to engineer spin polarization in 𝑑-wave altermagnets using gating, optical driving, and in-plane electric fields, which enable tunable and switchable polarizations along multiple directions. Optical driving induces out-of-plane (𝑧) polarization, while gating and in-plane fields generate 𝑥 and 𝑦 polarizations via the Edelstein effect, all of which are experimentally detectable. We further find that spin- and band-selective doping induces chiral optical activity, a feature unique to altermagnets. Our approach offers a versatile means to control the direction of spin polarization in altermagnets.

Floquet systems↗
DOE OSTI2021

NO x adsorption with CO and C 2 H 4 on Pd/SSZ-13: Experiments and modeling

A transient monolith model containing microkinetic schemes for NO uptake and release over Pd/SSZ-13 without and with reductants CO or C2H4 is presented. The scheme involves three cationic Pd species (Z – [PdOH] + , Z – Pd 2+ Z – , Z – Pd + ) as the active sites during uptake of NO, CO and C 2 H 4 , and their desorption and conversion at higher temperature. Kinetic parameters are estimated through a combination of density functional theory (DFT) estimates and a fit of uptake, desorption and conversion data. The tuned model is validated at different uptake temperatures, ramp rates, and flowrates. A “degree of uptake control” parameter is defined that helps to identify the step(s) that are uptake controlling. The model helps to interpret the data features and is used to identify operating conditions to meet application-relevant performance metrics, including NO trapping efficiency and NO release temperature. Furthermore, the model demonstrates higher NO uptake on Pd/SSZ-13 compared to Pd/ZSM-5.

42 ENGINEERING↗
DOE OSTI2020

Atomistic modeling of energy band alignment in CdSeTe surfaces

Atomistic modeling based on Desnity Functional Theory (DFT)- 1/2 method coupled with surface Green’s function has been employed to investigate the energy band alignment results in cadmium selenium telluride (CdSeTe) surfaces. The structural and electronic properties of the bulk ternary alloy were established before cleaving the CdSeTe low index surface facets. The dependency of atomic-scale electronic features on different plane orientations was explored by studying the energy band alignment diagrams in the unreconstructed and reconstructed surfaces. While the low index CdSeTe surface geometry reconstructions replicate the CdTe surface geometries, the energy band alignment features of the unreconstructed and reconstructed CdSeTe surfaces differ from those observed in CdTe low index surfaces. The structurally relaxed reconstructed CdSeTe surface results in purely flat bands as opposed to an internal cusp feature observed in CdTe surfaces. The presence of an internal energy cusp in CdTe(111) surfaces is expected to play a key role in enhancing the hole charge transport towards the back of CdTe-only solar cell device and the absence of such feature in CdSeTe surface may explain one of the reason for the lower performance of CdSeTe-only solar cell seen experimentally.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Investigating the origin of the far-field reflection interference fringe (RIF) of microdroplets

We show that the reflection interference fringe (RIF) is formed on a screen far away from the microdroplets placed on a prism-based substrate, which have low contact angles and thin droplet heights, caused by the dual convex–concave profile of the droplet, not a pure convex profile. The geometric formulation shows that the interference fringes are caused by the optical path difference when the reflected rays from the upper convex profile at the droplet–air interface interfere with reflection from the lower concave profile at oblique angles lower than the critical angle. Analytic solutions are obtained for the droplet height and the contact angle out of the fringe number and the fringe radius in RIF from the geometric formulation. Furthermore, the ray tracing simulation is conducted using the custom-designed code. The geometric formulation and the ray tracing show excellent agreement with the experimental observation in the relation between the droplet height and the fringe number and the relation between the contact angle and the fringe radius. This study is remarkable as the droplet's dual profile cannot be easily observed with the existing techniques. However, the RIF technique can effectively verify the existence of a dual profile of the microdroplets in a simple setup. In this work, the RIF technique is successfully developed as a new optical diagnostic technique to determine the microdroplet features, such as the dual profile, the height, the contact angle, the inflection point, and the precursor film thickness, by simply measuring the RIF patterns on the far-field screen.

42 ENGINEERING↗
DOE OSTI2022

Turbulent Rotating Rayleigh–Bénard Convection

Rotation with thermally induced buoyancy governs many astrophysical and geophysical processes in the atmosphere, ocean, sun, and Earth's liquid-metal outer core. Rotating Rayleigh–Bénard convection (RRBC) is an experimental system that has features of rotation and buoyancy, where a container of height H and temperature difference Δ between its bottom and top is rotated about its vertical axis with angular velocity Ω. The strength of buoyancy is reflected in the Rayleigh number (~ H 3 Δ) and that of the Coriolis force in the Ekman and Rossby numbers (~Ω -1 ). Rotation suppresses the convective onset, introduces instabilities, changes the velocity boundary layers, modifies the shape of thermal structures from plumes to vortical columns, affects the large-scale circulation, and can decrease or enhance global heat transport depending on buoyant and Coriolis forcing. RRBC is an extremely rich system, with features directly comparable to geophysical and astrophysical phenomena. Here we review RRBC studies, suggest a unifying heat transport scaling approach for the transition between rotation-dominated and buoyancy-dominated regimes in RRBC, and discuss non-Oberbeck–Boussinesq and centrifugal effects.

42 ENGINEERING↗
DOE OSTI2021

Conventional Rib Turbulators For SCO 2 Turbine Internal Cooling (Report)

This report documents experimental work in the NETL Heat Exchange and Experimental Testing (HEET) rig. The heat transfer performance of additively manufactured internal cooling features in supercritical CO 2 were characterized. It was demonstrated that the thermal performance factor of conventional angled rib turbulators remains independent of Reynolds number up to 3.1 x 10 5 indicating that these features may be employed to enhance heat transfer in sCO 2 turbine blades and vanes. This augmentation of heat transfer in the internal cooling passages decreases the required turbine coolant and improves the power cycle efficiency.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2026

Statistical and Machine Learning Approaches to Analyzing Pipeline Incidents in the United States (2010–2024)

This study applies machine learning methods to analyze natural gas pipeline incidents in the United States using the Pipeline and Hazardous Materials Safety Administration (PHMSA) Gas Distribution Incident Dataset (2010–2024). The dataset includes over 600 variables describing incident characteristics, infrastructure attributes, and contributing factors associated with unintentional gas releases. The objective is to assess whether these features can reliably predict the underlying cause of pipeline failures. Multinomial logistic regression and Random Forest models were developed to classify incident causes, including excavation damage, corrosion, equipment failure, and natural forces. Results show that excavation damage is both the most frequent and most predictable cause, with models achieving strong performance for this category. However, when excavation damage is excluded, model accuracy declines significantly, with some models performing near random levels. Across all approaches, severe class imbalance and limited variability in key predictors constrain predictive performance. Pipeline age and diameter emerge as the most influential variables, but they provide insufficient discriminatory power to distinguish among less frequent failure types. These findings indicate that non-excavation-related incidents are rare, heterogeneous, and weakly represented in the dataset, limiting the effectiveness of machine learning classification. Overall, this study highlights the structural limitations of the PHMSA dataset for predictive modeling and underscores the need for improved data balance and feature enrichment. The results reinforce excavation damage prevention as the most impactful strategy for reducing pipeline incidents.

03 NATURAL GAS↗
DOE OSTI2020

Biosystems Design by Machine Learning

Biosystems such as enzymes, pathways, and whole cells have been increasingly explored for biotechnological applications. Yet, the intricate connectivity and complexity of biosystems pose a major hurdle in designing biosystems with desired features. As -omics and other high throughput technologies have been rapidly developed, the promise of applying machine learning (ML) techniques in biosystems design has started to become a reality. ML models enable the identification of patterns within complicated biological data across multiple scales of analysis and can augment biosystems design applications by predicting new candidates for optimized performance. ML is being used at every stage of biosystems design to help find non-obvious engineering solutions with fewer design iterations. In this review, we first describe commonly used models and modeling paradigms within ML. We then discuss some applications of these models that have already shown success in biotechnological applications. Moreover, we discuss successful applications at all scales of biosystems design, including nucleic acids, genetic circuits, proteins, pathways, genomes, and bioprocess. Lastly, we discuss some limitations of these methods and potential solutions as well as prospects of the combination of ML and biosystems design.

59 BASIC BIOLOGICAL SCIENCES↗