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DOE OSTI2023

Understanding the evolution of double perovskite band structure upon dimensional reduction

Recent investigations into the effects of dimensional reduction on halide double perovskites have revealed an intriguing change in band structure when the three-dimensional (3D) perovskite is reduced to a two-dimensional (2D) perovskite with inorganic sheets of monolayer thickness (n = 1). The indirect bandgap of 3D Cs 2 AgBiBr 6 becomes direct in the n = 1 perovskite whereas the direct bandgap of 3D Cs 2 AgTlBr 6 becomes indirect at the n = 1 limit. Here, we apply a linear combination of atomic orbitals approach to uncover the orbital basis for this bandgap symmetry transition with dimensional reduction. We adapt our previously established method for predicting band structures of 3D double perovskites for application to their 2D congeners, emphasizing new considerations required for the 2D lattice. In particular, we consider the inequivalence of the terminal and bridging halides and the consequences of applying translational symmetry only along two dimensions. The valence and conduction bands of the layered perovskites can be derived from symmetry adapted linear combinations of halide p orbitals propagated across the 2D lattice. The dispersion of each band is then determined by the bonding and antibonding interactions of the metal and halide orbitals, thus affording predictions of the essential features of the band structure. We demonstrate this analysis for 2D Ag–Bi and Ag–Tl perovskites with sheets of mono- and bilayer thickness, establishing a detailed understanding of their band structures, which enables us to identify the key factors that drive the bandgap symmetry transitions observed at the n = 1 limit. Importantly, these insights also allow us to make the general prediction that direct → indirect or indirect → direct bandgap transitions in the monolayer limit are most likely in double perovskite compositions that involve participation of metal d orbitals at the band edges or that have no metal-orbital contributions to the valence band, laying the groundwork for the targeted realization of this phenomenon.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2024

Harnessing Collaborative Learning Automata to Guide Multi-objective Optimization based Inverse Analysis for Structural Damage Identification

Structural damage identification based on physical models is often transformed into an optimization problem that minimizes the difference between measurement information of structure being monitored and the model prediction in the parametric space. However, the objective function in this context often exhibits multimodality, involving high-dimensional variables due to the reliance on finite element models for damage identification. These features pose challenges to optimization algorithms, where entrapment in local solutions can lead to false positives and false negatives in damage identification. In this research, we propose a reinforcement learning based multi-swarm optimizer to tackle such challenges in pursuit of a small yet diverse solution set that can capture the true damage scenario as one of the solutions. The proposed method leverages the flexibility of the particle swarm optimizer and incorporates novel strategies of metaheuristics to realize targeted improvement. To enable the particle swarm to adaptively select the appropriate search strategy based on the current environment, we adopt the learning automata technique, which sidesteps the need for reward strategy selection that is usually ad hoc at each step of the search. The integration harnesses the automatic learning and self-adaptation capabilities of learning automata, enabling the particles to navigate based on environmental signals. This leads to accumulated probabilities tied to advantageous movements, fostering an adaptive exploration of particles in the search space. The proposed approach is first validated through implementing into benchmark test cases with comparisons. It is then applied to structural damage identification with piezoelectric admittance experimental signals. `The results highlight the capability of the algorithm to identify a small solution set with high accuracy to match the actual damage scenario.

Yang Zhang↗

NASA NTRS2017

R2U2: Tool Overview

R2U2 (Realizable, Responsive, Unobtrusive Unit) is an extensible framework for runtime System HealthManagement (SHM) of cyber-physical systems. R2U2 can be run in hardware (e.g., FPGAs), or software; can monitorhardware, software, or a combination of the two; and can analyze a range of different types of system requirementsduring runtime. An R2U2 requirement is specified utilizing a hierarchical combination of building blocks: temporal formula runtime observers (in LTL or MTL), Bayesian networks, sensor filters, and Boolean testers. Importantly, the framework is extensible; it is designed to enable definitions of new building blocks in combination with the core structure. Originally deployed on Unmanned Aerial Systems (UAS), R2U2 is designed to run on a wide range of embedded platforms, from autonomous systems like rovers, satellites, and robots, to human-assistive ground systems and cockpits. R2U2 is named after the requirements it satisfies; while the exact requirements vary by platform and mission, the ability to formally reason about realizability, responsiveness, and unobtrusiveness is necessary for flight certifiability, safety-critical system assurance, and achievement of technology readiness levels for target systems. Realizability ensures that R2U2 is suficiently expressive to encapsulate meaningful runtime requirements while maintaining adaptability to run on different platforms, transition between different mission stages, and update quickly between missions. Responsiveness entails continuously monitoring the system under test, real-time reasoning, reporting intermediate status, and as-early-as-possible requirements evaluations. Unobtrusiveness ensures compliance with the crucial properties of the target architecture: functionality, certifiability, timing, tolerances, cost, or other constraints.

Rozier, Kristin Y.↗

NASA NTRS2019

Conceptual Design of a Counter-Rotating Fan System for Distributed Boundary Layer Ingesting Propulsion

The present paper details the design of the counter rotating fans for a Turboelectric Distributed Propulsion (TeDP) system. Sixteen propulsors installed in mail-slot-shape nacelles are embedded on an aerodynamically optimized hybrid wing-body configuration. The hybrid-wing/body (HWB) configuration which was previously designed to satisfy the conditions of trim, longitudinally static stability and specific cargo space is employed as the baseline configuration in pursuing an optimal distributed propulsion system. A set of distributed propulsors is conceptually designed and the collective performance is evaluated against the target thrust mandated by the mission requirements. The concept of the distributed propulsion allows the fan pressure ratio to be around 1.27~1.32 for the target thrust. In addition, further splitting of the fan pressure ratio by using the counter-rotating fans for each slot realizes the target pressure ratio with low tip speed. In the distributed propulsion system, the nature of the flow conditions and/or the thickness of the ingested boundary layer may differ and result in different propulsive reaction of each individual propulsor. The optimization is, thus, approached from both the propulsion system and individual propulsor perspectives. An optimal distribution of the thrust and power output is determined by how the system utilizes each passage's propulsive characteristics and its interaction with the airframe. These system level analysis and optimization are conducted using an actuator disk model to account for the propulsion-airframe integration numerically. With respect to the propulsor level, aerodynamic shape optimizations of the fan blades are performed in a sequential multi-objective optimization process for various design objectives, such as mass flow rate condition, fan pressure ratio, efficiency and the exit flow angle of the fan stage by using a genetic algorithm, NSGA-II. The radial chord distribution, and meanline distribution of the rotors are designed on the circumferentially averaged axi-symmetric inlet profiles and tested on the six inlet profiles from six divided sectors to reckon flow distortion. The performances of the counter rotating fans are, thus, evaluated accordingly for obtaining distortion tolerant fan. The performance of the distributed propulsion system is evaluated by two CFD tools, i.e., a multi-stage turbo-machinery CFD code and one propulsion-airframe integration flow solver coupled with a body-force model. The optimized boundary layer ingestion propulsion system of 16 distributed slots not only reaches the system target thrust, but also delivers a close to 20% fuel saving benefit against its counterpart 12 distributed clean inlet propulsion system.

Boundary-Layer-Ingestion Propulsion↗

DOE OSTI2024

Human-Centered and Explainable Artificial Intelligence in Nuclear Operations

Nuclear power plants in the United States are critical to the nation’s energy security, accounting for 20% of all electricity produced for the power grid. As energy needs grow, 100 gigawatts of additional nuclear power will be necessary by 2050, more than double the current capacity. Realizing this target requires cutting-edge technology like artificial intelligence (AI) and machine learning (ML) that can bring about significant increases in the level of automation. Human-centered AI (HCAI) is a combination of human-centered design (human factors, human-in-the-loop, etc.) with AI/ML to help produce an efficient and reliable system with full consideration for human engagement. This paper provides a comprehensive and novel discussion of HCAI considerations in nuclear power, introducing unique applications for the existing fleet as well as new advanced reactor designs. We include real-life use cases of AI applications to work management processes at nuclear power sites and highlight lessons learned for HCAI.

Hall, Anna↗

DOE OSTI2026

A Charge-Agnostic Design for 6D Muon Ionization Cooling

A muon collider presents a compelling path forward for high-energy physics, offering both energy reach and precision. The notable challenge in realizing the target luminosities for a muon collider is in the development of a sufficiently fast cooling scheme — one capable of several orders of magnitude in emittance reduction with minimal decay losses. Ionization cooling is presently considered the only scheme to fit this criterion. Traditional ionization cooling channels are characterized by a solenoid-based lattice for beam focusing and a low-Z absorbing material wherein the beam deposits energy via ionization. Dipole fields are used to generate dispersion such that higher-momentum muons pass through more absorbing material, enabling 6D cooling by leveraging emittance exchange. The problem with this approach is the charge-specificity of the dispersion function, necessitating separate channels for $\mu^+$ and $\mu^-$. Here, the Helical FOFO Snake (HFOFO) is presented as an alternative approach to 6D cooling that agnostically treats both signs of muon, enabling a single cooling channel for both.

Riggall, Caroline [Tennessee U.] (ORCID:0009000849↗

DOE OSTI2025

Variable Curvature Pultruded Vertical Axis Wind Blades

XFlow Energy is developing a floating offshore vertical-axis wind turbine (VAWT) enabling a 70% reduction in the levelized cost of energy compared to floating horizontal-axis wind turbines (HAWTs). While the wind industry has historically been successful at lowering the cost of terrestrial wind systems, there are no scalable, economically viable floating wind solutions on the market with the levelized cost of energy (LCOE) of current floating offshore solutions is $200/MWh (Musial 2022). Low-cost blade production is one of the key technologies for realizing this target LCOE reduction. The proposed design uses a constant cross-section blade, enabling the use of pultrusion, a continuous, automated, mold-free production method. By employing blades with variable curvature, XFlow can minimize the bending stresses in the blades, allowing for light-weighting. Constant curvature pultrusion has been demonstrated on hollow sections. Variable curvature pultrusion has been demonstrated on solid sections. This project aims to develop a method of variable curvature pultrusion for hollow sections, as required for mass-optimal VAWT blades.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

Variable Curvature Pultruded Vertical Axis Wind Blades

XFlow Energy is developing a floating offshore vertical-axis wind turbine (VAWT) enabling a 70% reduction in the levelized cost of energy compared to floating horizontal-axis wind turbines (HAWTs). While the wind industry has historically been successful at lowering the cost of terrestrial wind systems, there are no scalable, economically viable floating wind solutions on the market with the levelized cost of energy (LCOE) of current floating offshore solutions is $\$$200/MWh (Musial 2022). Low-cost blade production is one of the key technologies for realizing this target LCOE reduction. The proposed design uses a constant cross-section blade, enabling the use of pultrusion, a continuous, automated, mold-free production method. By employing blades with variable curvature, XFlow can minimize the bending stresses in the blades, allowing for light-weighting. Constant curvature pultrusion has been demonstrated on hollow sections. Variable curvature pultrusion has been demonstrated on solid sections. This project aims to develop a method of variable curvature pultrusion for hollow sections, as required for mass-optimal VAWT blades.

17 WIND ENERGY↗

NASA NTRS2018

Conceptual Aerodynamic Design of a Tail-Cone Thruster System Under Axi-Symmetric Inlet Distortion

This paper presents a conceptual design of a tail-cone thruster system which is operating under an axisymmetric inlet distortion. An effort to realize the targeted fuel burn saving that was proposed in NASA's STARC_ABL aircraft design is made through a CFD (Computational Fluid Dynamics)-based design approach. This method employs three iterative steps to exploit the CFD tools until the design requirements are met: a quasi-2D through-flow model to design the fan/EGV (Exit Guide Vane), a 3-D RANS (Reynolds Averaging Navier-Stokes) simulation of the single blade row to account for the inlet/fan and the EGV/nozzle interaction, and a 3-D RANS simulation of the airframe with a propulsor installed - propulsion airframe integration (PAI). The design requirements which include the thrust, and shaft power of the propulsor are matched throughout the evaluations coming from two CFD domains, i.e., the turbo-machinery and the PAI. During the switch between these different computational domains, the inlet and exit profiles are matched via the correction factors of the body-force model. The present tail-cone thruster (TCT) aerodynamic design leverages a low-pressure ratio fan (FPR=1.2 to approximately 1.25) of which the camber-line angles are predicted by a quasi-2D through-flow model. The quasi-2D model is derived to analyze the radially distorted flow resulting from the ingested boundary layer at the inlet. It also estimates the appropriate velocity vectors of the metal angles of the fan and EGV which is subjected to different types of vortex at the fan exit. The baseline geometry is revisited and its internal flow-path and exhaust cone are redesigned to illustrate the strong correlation among the components of the propulsor in the PAI domain. The peak efficiency point of the fan/EGV with respect to the blade counts, also known as solidity, and rotational speed is chosen for the cruise condition via parametric studies. The corresponding performance maps are presented. The resulting performance metrics of the new conceptual design of the BLI (Boundary Layer Ingestion) propulsor are analyzed and compared with these of the baseline in the PAI aspect. Finally, ideas of the CFD based design of a BLI propulsor are discussed based on the observations drawn from the numerical results.

Inlet↗

DOE OSTI2025

Informed total-error-minimizing priors: Interpretable cosmological parameter constraints despite complex nuisance effects

While Bayesian inference techniques are standard in cosmological analyses, it is common to interpret resulting parameter constraints with a frequentist intuition. This intuition can fail, for example, when marginalizing high-dimensional parameter spaces onto subsets of parameters, because of what has come to be known as projection effects or prior volume effects. We present the method of informed total-error-minimizing (ITEM) priors to address this problem. An ITEM prior is a prior distribution on a set of nuisance parameters, such as those describing astrophysical or calibration systematics, intended to enforce the validity of a frequentist interpretation of the posterior constraints derived for a set of target parameters (e.g., cosmological parameters). Our method works as follows. For a set of plausible nuisance realizations, we generate target parameter posteriors using several different candidate priors for the nuisance parameters. We reject candidate priors that do not accomplish the minimum requirements of bias (of point estimates) and coverage (of confidence regions among a set of noisy realizations of the data) for the target parameters on one or more of the plausible nuisance realizations. Of the priors that survive this cut, we select the ITEM prior as the one that minimizes the total error of the marginalized posteriors of the target parameters. As a proof of concept, we applied our method to the density split statistics measured in Dark Energy Survey Year 1 data. We demonstrate that the ITEM priors substantially reduce prior volume effects that otherwise arise and that they allow for sharpened yet robust constraints on the parameters of interest.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Synthesis and Characterization of Metastable Cobalt Honeycomb KCoAsO 4

The Kitaev model has served as a long-sought-after target in the realization of a quantum spin liquid that could host Majorana Fermions. Such non-Abelian anyons could revolutionize quantum computing if properly implemented to overcome decoherence. A 3d 7 electronic configuration, like Co 2+ , has been explored by theory and experimental work to design Kitaev materials. Here, in this study, we report the synthesis of a new cobaltate honeycomb material KCoAsO 4 . The compound is synthesized through a low-temperature solution route and crystallized in space group R¯3 with lattice parameters a = 5.0394(1) and c = 28.6790(1) as determined by neutron powder diffraction. The crystal structure follows motifs similar to those of the honeycomb compound BaCo2(AsO 4 ) 2 but presents differing magnetic behavior. Magnetization/heat capacity measurements on the powder show antiferromagnetic transition T N = 14 K. Two lower-temperature transitions are present in susceptibility at low field that resemble spin reorientations. Magnetization data as a function of field have curvature indicative of metamagnetic behavior below the magnetic ordering temperature, with the magnetic ordering suppressed upon application of a higher magnetic field. Computational studies suggest the presence of a weak nearest-neighbor Kitaev term, K 1 , consistent with related honeycomb cobaltates. Together, the data suggest that this material should present a new platform for developing Kitaev quantum spin liquids.

cobaltate↗

DOE OSTI2026

Improving indirect-drive ablator performance through pulse shaping and material selection in double shell implosions

The double shell path to inertially confined volumetric thermonuclear burn relies on efficient kinetic energy transfer from an outer ablator shell to an inner shell containing DT fuel at implosion velocities near 250 km/s. In order to experimentally realize adequate compression, target imperfections and assembly features must be tightly controlled. Pulse shape and ablator material are critical design choices that impact all aspects of the implosion. In this article, we evaluate three designs: an Al ablator with single-shock radiation drive, a CH ablator with single-shock drive, and a CH ablator with reduced-adiabat 2-shock drive. All designs use the same W inner (pusher) shell overcoated with a glow discharge polymer tamper and filled with liquid-density DT. One-dimensional HYDRA simulations revealed that the plastic ablator design required the use of the 2-shock drive to match the performance of the Al design. Two-dimensional simulations resolving broadband surface roughness up to modes of several hundred placed only on the ablator showed plastic to greatly outperform Al. The plastic ablator designs did exhibit higher levels of inner shell instability growth when surface roughness was only placed at the pusher/tamper interface, which was mitigated with higher foam cushion densities. A unique and additional benefit of a plastic ablator is also discussed, where heating of the ablator by Au M-band radiation is predicted to rapidly expand the hemi-shell surfaces, closing the equatorial joint gap ahead of the first shock. Taken together, the properties of the plastic ablator for indirect-drive double shell implosions appear promising in removing several long-standing fabrication challenges.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Diagnosing inertial confinement fusion ignition

Abstract Fusion ignition by inertial confinement requires compression and heating of the fusion fuel to temperatures in excess of 5 keV and densities exceeding hundreds of g/cc. In August 2021, this scientific milestone was surpassed at the National Ignition Facility (NIF), when the Lawson criterion for ignition was exceeded generating 1.37MJ of fusion energy (Abu-Shawareb et al 2022 Phys. Rev. Lett. 129 075001), and then in December 2022 target gain >1 was realized with the production of 3.1MJ of fusion energy from a target driven by 2.0MJ of laser energy (Abu-Shawareb et al 2024 Phys. Rev. Lett. 132 065102). At the NIF, inertial confinement fusion research primarily uses a laser indirect drive in which the fusion capsule is surrounded by a high-Z enclosure (‘hohlraum’) used to convert the directed laser energy into a symmetric x-ray drive on the capsule. Precise measurements of the plasma conditions, x-rays, γ -rays and neutrons produced are key to understanding the pathway to higher performance. This paper discusses the diagnostics and measurement techniques developed to understand these experiments, focusing on three main topics: (1) key diagnostic developments for achieving igniting plasmas, (2) novel signatures related to thermonuclear burn and (3) advances to diagnostic capabilities in the igniting regime with a perspective toward developments for intertial fusion energy.

Moore, A. S. (ORCID:0000000221258882)↗

NASA NTRS1988

Laser investigations for payload G-652 prior to filing pre-flight accommodation requirements

In anticipation of presenting the preflight accommodations requirements to NASA for approval, the physics, biology, electronic and chemistry aspects of laser experiments which are most advantageous to the flight are investigated. Preliminary laboratory evaluation was targeted with the realization that future flights of the shuttle may begin in 1988. It is the consensus that during the holding time before the resumption of flights, there is an extra margin of perfection which is possible and that the period prior to flight is advantageous technologically. The problems that can be encountered in space flown laser systems are addressed and the analysis of data is offered as a model for preflight accommodation requirement filing.

Bellina, Joseph↗

NASA NTRS2006

Intelligent Vision Systems Independent Research and Development (IR&D) 2006

This report summarizes results in conduct of research sponsored by the 2006 Independent Research and Development (IR&D) program at Marshall Space Flight Center (MSFC) at Redstone Arsenal, Alabama. The focus of this IR&D is neural network (NN) technology provided by Imagination Engines, Incorporated (IEI) of St. Louis, Missouri. The technology already has many commercial, military, and governmental applications, and a rapidly growing list of other potential spin-offs. The goal for this IR&D is implementation and demonstration of the technology for autonomous robotic operations, first in software and ultimately in one or more hardware realizations. Testing is targeted specifically to the MSFC Flat Floor, but may also include other robotic platforms at MSFC, as time and funds permit. For the purpose of this report, the NN technology will be referred to by IEI's designation for a subset configuration of its patented technology suite: Self-Training Autonomous Neural Network Object (STANNO).

Patrick, Clinton↗

DOE OSTI2026

Exploring the holographic entropy cone via reinforcement learning

We develop a reinforcement learning algorithm to study the holographic entropy cone. Given a target entropy vector, our algorithm searches for a graph realization whose min-cut entropies match the target vector. If the target vector does not admit such a graph realization, it must lie outside the cone, in which case the algorithm finds a graph whose corresponding entropy vector most nearly approximates the target and allows us to probe the location of the facets. For the N = 3 cone, we confirm that our algorithm successfully rediscovers monogamy of mutual information beginning with a target vector outside the holographic entropy cone. We then apply the algorithm to the N = 6 cone, analyzing the 6 mystery extreme rays of the subadditivity cone from [1] that satisfy all known holographic entropy inequalities yet lacked graph realizations. We found realizations for 3 of them, proving they are genuine extreme rays of the holographic entropy cone, while providing evidence that the remaining 3 are not realizable, implying unknown holographic inequalities exist for N = 6.

AdS-CFT correspondence↗

DOE OSTI2026

Computationally designed coiled coil ‘bundlemers’ as model colloidal nanoparticles for solution assembly and materials design (Final Report)

As a collaborative team at the University of Delaware and the University of Pennsylvania, Kloxin, Pochan and Saven designed new biomimetic nanomaterials de novo, leveraging a variety of complementary areas of expertise: computational design of biopolymers (Saven at the University of Pennsylvania), and synthesis and characterization (Kloxin and Pochan at the University of Delaware). Overall activities included: sequence-specific peptide synthesis; covalent crosslinking; noncovalent assembly; site-specific functionalization; and nanostructural characterization using electron microscopy and solution-phase (x-ray and neutron) scattering. Using natural and non-natural amino acids, the team created modular, functional peptide building blocks for elaboration of new nanostructured materials. Ultimately, the development of robust peptide-based, building blocks provides tools for researchers to readily produce complex nanomaterial structures in a wide range of applications. The project had three, interconnecting goals in an effort to provide the broader scientific community with a new peptide-based paradigm for materials design and characterization. First, we further developed the coiled-coil bundle-based toolbox (otherwise known as the ‘bundlemer’ toolbox) via computational design with experimental bundle assembly verification. Second, we developed new uses of covalent interactions, in addition to desired physical (noncovalent) interactions, to assemble bundlemers into 1-D polymer chains with targeted chain rigidity, length, and dispersity. Thirds, we used the above designs to experimentally realize (physical or covalent) polymers to target the creation of liquid crystals or to realize interparticle assembly into nanoporous lattices. The close integration of the three groups was instrumental in success of the biomolecular materials design, formation, and understanding for future designs.

36 MATERIALS SCIENCE↗

NASA NTRS1992

Automation of the targeting and reflective alignment concept

The automated alignment system, described herein, employs a reflective, passive (requiring no power) target and includes a PC-based imaging system and one camera mounted on a six degree of freedom robot manipulator. The system detects and corrects for manipulator misalignment in three translational and three rotational directions by employing the Targeting and Reflective Alignment Concept (TRAC), which simplifies alignment by decoupling translational and rotational alignment control. The concept uses information on the camera and the target's relative position based on video feedback from the camera. These relative positions are converted into alignment errors and minimized by motions of the robot. The system is robust to exogenous lighting by virtue of a subtraction algorithm which enables the camera to only see the target. These capabilities are realized with relatively minimal complexity and expense.

Redfield, Robin C.↗