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At least 271 records · Page 15

Anomalous elastic softening in ferroelectric hafnia under pressure

his study employs first-principles density-functional theory (DFT) calculations to explore the elastic and mechanical properties of ferroelectric hafnia (HfO 2 ) in its polar orthorhombic 𝑃⁢𝑐⁢𝑎⁢2 1 phase under varying hydrostatic pressure conditions up to 30 GPa. Utilizing a plane-wave basis set and Perdew-Burke-Ernzerhof generalized-gradient approximation for solids in our DFT calculations, we investigate both pure and yttrium-substituted HfO 2 . Our findings reveal an anomalous reduction in the 𝐶 33 component of the elastic tensor with increasing pressure, which becomes significant above 15 GPa and signals a potential pressure-driven structural phase transition at higher pressure. The analysis of atomic displacements under pressure sheds light on the unusual mechanical behavior and phase stability of this material. Additionally, we observe a transition from an indirect band gap to a direct band gap with increasing pressure, which could have significant implications for optical applications. Here, the effects of yttrium substitution on the mechanical and electronic properties are further examined, revealing that yttrium substitution softens the elastic response of this material and reduces the electronic band gap. These results enhance our understanding of elastic and mechanical responses of ferroelectric hafnia and its potential for applications in microelectronics, piezoelectric devices, and nonvolatile ferroelectric random-access memories. Further experimental validation is recommended to confirm our predictions and explore the practical implications of the observed phase transitions and electronic behavior of the ferroelectric hafnia under high-pressure conditions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

The Influence of Unsteadiness on the Analysis of Pressure Gain Combustion Devices

Pressure gain combustion (PGC) has been the object of scientific study for over a century due to its promise of improved thermodynamic efficiency. In many recent application concepts PGC is utilized as a component in an otherwise continuous, normally steady flow system, such as a gas turbine or ram jet engine. However, PGC is inherently unsteady. Failure to account for the effects of this periodic unsteadiness can lead to misunderstanding and errors in performance calculations. This paper seeks to provide some clarity by presenting a consistent method of thermodynamic cycle analysis for a device utilizing PGC technology. The incorporation of the unsteady PGC process into the conservation equations for a continuous flow device is presented. Most importantly, the appropriate method for computing the conservation of momentum is presented. It will be shown that proper, consistent analysis of cyclic conservation principles produces representative performance predictions.

Paxson, Daniel E.↗

Overcoming persistent challenges in putting environmental flow policy into practice: a systematic review and bibliometric analysis

The implementation of environmental flows (e-flows) aims to reduce the negative impacts of hydrological alteration on freshwater ecosystems. Despite the growing attention to the importance of e-flows since the 1970s, actual implementation has lagged. Therefore, we explore the limitations in e-flows implementation, their systemic reasons, and solutions. We conducted a systematic review and a bibliometric analysis to identify peer-reviewed articles published on the topic of e-flows implementation research in the last two decades, resulting in 68 research and review papers. Co-occurrence of terms, and geographic and temporal trends were analyzed to identify the gaps in environmental water management and propose recommendations to address limitations on e-flows implementation. We identify the underlying causes and potential solutions to such challenges in environmental water management. The limitations to e-flow implementation identified were categorized into 21 classes. The most recognized limitation was the competing priorities of human uses of water (n = 29). Many secondary limitations, generally co-occurring in co-causation, were identified as limiting factors, especially for implementing more nuanced and sophisticated e-flows. The lack of adequate hydrological data (n = 24) and ecological data (n = 28) were among the most mentioned, and ultimately lead to difficulties in starting or continuing monitoring/adaptive management (n = 28) efforts. The lack of resource/capacity (n = 21), experimentation (n = 19), regulatory enforcement (n = 17), and differing authorities involved (n = 18) were also recurrent problems, driven by the deficiencies in the relative importance given to e-flows when facing other human priorities. In order to provide a clearer path for successful e-flow implementation, system mapping can be used as a starting point and general-purpose resource for understanding the sociohydrological problems, interactions, and inherited complexity of river systems. Secondly, we recommend a system analysis approach to address competing demands, especially with the use of coupled water-energy modeling tools to support decision-making when hydropower generation is involved. Such approaches can better assess the complex interactions among the hydrologic, ecological, socioeconomic, and engineering dimensions of water resource systems and their effective management. Lastly, given the complexities in environmental water allocation, implementation requires both scientific rigor and proven utility. Consequently, and where possible, we recommend a move from simplistic flow allocations to a more holistic approach informed by hydroecological principles. To ease conflicts between competing water demands, water managers can realize more 'pop per drop' by supporting key components of a flow regime that include functional attributes and processes that enhance biogeochemical cycling, structural habitat formation, and ecosystem maintenance.

54 ENVIRONMENTAL SCIENCES↗

Recursive Use of the Short-Time Fast Fourier Transform for Signature Analysis in Continuous Processes

Although a nuclear reactor is a hostile environment for sensing and electrical communications, the reactor core is amenable to acoustic communication. An acoustic measurement infrastructure (AMI) has been installed in the Advanced Test Reactor (ATR) to record acoustic signals that can capture its different operating regimes. AMI uses coolant pumps as continuous signal sources, coolant and structural components as transmission lines, and accelerometers to capture system motion. A recursive signal processing technique based on the short-time fast Fourier transform (STFFT) for continuous processes provides unique signatures for diagnostic and prognostic analyses from the system motion data. Here this article presents a recursive STFFT methodology that processes acoustic signals from continuous industrial processes. The article first discusses the initial STFFT use with simulated data to elucidate the basic principles necessary to understand and interpret the STFFT results from actual pump vibration data. Each repetitive use of the STFFT on pump vibration data using the results from the prior STFFT processing will generate additional complimentary time-frequency-based signatures. These signatures are generated by the coolant pumps operating under different process conditions. After each use of the STFFT, the resulting signatures provide exemplary examples of the diversity and intuitive nature of recursively using the STFFT. This article focuses on recursively using the STFFT to provide numerous complimentary and diverse signatures that will ultimately be inputs for machine learning algorithms that provide predictive data analytics. The intuitive nature of the information and signatures from recursive STFFT processing will also bring intuitive interpretation capabilities to machine learning and predictive data analytic techniques.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Configurational stability of a crack propagating in a material with mode-dependent fracture energy – Part II: Drift of fracture facets in mixed-mode I+II+III

In earlier papers (Leblond et al., 2011; 2019), we presented linear stability analyses of the coplanar propagation of a crack loaded in mixed-mode I+III, based on a “double” propagation criterion combining (Griffith, 1920)’s energetic condition and (Goldstein and Salganik, 1974)’s principle of local symmetry. The difference between the two papers was that in the more recent one, the local value of the critical energy-release-rate was no longer considered as a constant, but heuristically allowed to depend upon the ratio of the local mode III to mode I stress intensity factors. This led to a much improved, qualitatively acceptable agreement of theory and experiments, for the “threshold” value of the ratio of the unperturbed mode III to mode I stress intensity factors, above which coplanar propagation becomes unstable. In this paper, the analysis is extended to the case where a small additional mode II loading component is present in the initially planar configuration of the crack, generating a small, general kink of this crack from the moment it is applied. The main new effect resulting from presence of such a loading component is that the instability modes present above the threshold must drift along the crack front during its propagation. This prediction may be useful for future theoretical interpretations of a number of experiments where such a drifting motion was indeed observed.

36 MATERIALS SCIENCE↗

Analysis of Cutter Blade Wear in Rotary Shear Mills

Following development of an analytical abrasive wear model to predict wear of components in a rotary shear mill, the team used a finite element analysis (FEA) approach to calculate forces and loads acting on particles responsible for abrasive wear. The analytical model related critical rotary shear process parameters (shear geometry and rotational speed) to critical material attributes of inorganic mineral species in feedstock (density, size, and aspect ratio) and substrate (hardness and elastic modulus) that enabled us to model the wear of shear cutters in a rotary shear milling system developed by Forest Concepts. With proper knowledge of the forces acting between abrasive particles and cutter components built into it, the model can accurately predict wear of the cutters and provides a quality by design (QbD) approach to predict component reliability based on scientific engineering principles in lieu of trial-and-error approaches. During this reporting period, researchers at Oak Ridge National Laboratory applied an FEA package to simulate the local stresses and forces between an abrasive silica particle and two rotary shear cutters as the distance between the cutters decreases. The output of the FEA was used to provide more accurate projections of the loads applied to the particles in the analytical wear model. Comparison of the FEA force calculations are in good agreement with the loads assumed in the analytical predictions.

36 MATERIALS SCIENCE↗

Polarization Imaging Apparatus

A polarization imaging apparatus has shown promise as a prototype of instruments for medical imaging with contrast greater than that achievable by use of non-polarized light. The underlying principles of design and operation are derived from observations that light interacts with tissue ultrastructures that affect reflectance, scattering, absorption, and polarization of light. The apparatus utilizes high-speed electro-optical components for generating light properties and acquiring polarization images through aligned polarizers. These components include phase retarders made of OptoCeramic (registered TradeMark) material - a ceramic that has a high electro-optical coefficient. The apparatus includes a computer running a program that implements a novel algorithm for controlling the phase retarders, capturing image data, and computing the Stokes polarization images. Potential applications include imaging of superficial cancers and other skin lesions, early detection of diseased cells, and microscopic analysis of tissues. The high imaging speed of this apparatus could be beneficial for observing live cells or tissues, and could enable rapid identification of moving targets in astronomy and national defense. The apparatus could also be used as an analysis tool in material research and industrial processing.

Zou, Yingyin K.↗

Rocket-Induced Magnetohydrodynamic Ejector: A Single-Stage-to-Orbit Advanced Propulsion Concept

During the atmospheric boost phase of a rocket trajectory, magnetohydrodynamic (MHD) principles can be utilized to augment the thrust by several hundred percent without the input of additional energy. The concept is an MHD implementation of a thermodynamic ejector. Some ejector history is described and some test data showing the impressive thrust augmentation capabilities of thermodynamic ejectors are provided. A momentum and energy balance is used to derive the equations to predict the MHD ejector performance. Results of these equations are compared with the test data and then applied to a specific performance example. The rocket-induced MHD ejector (RIME) engine is described and a status of the technology and availability of the engine components is provided. A top level vehicle sizing analysis is performed by scaling existing MHD designs to the required flight vehicle levels. The vehicle can achieve orbit using conservative technology. Modest improvements are suggested using recently developed technologies, such as superconducting magnets, which can improve predicted performance well beyond those expected for current single-stage-to-orbit (SSTO) designs.

Cole, John↗

A Historical Analysis of Crane Mishaps at Kennedy Space Center

Cranes and hoists are widely used in many areas. Crane accidents and handling mishaps are responsible for injuries, costly equipment damage, and program delays. Most crane accidents are caused by preventable factors. Understanding these factors is critical when designing cranes and preparing lift plans. Analysis of previous accidents provides insight into current recommendations for crane safety. Cranes and hoists are used throughout Kennedy Space Center to lift everything from machine components to critical flight hardware. Unless they are trained crane operators, most NASA employees and contractors do not need to undergo specialized crane training and may not understand the safety issues surrounding the use of cranes and hoists. A single accident with a crane or hoist can injure or kill people, cause severe equipment damage, and delay or terminate a program. Handling mishaps can also have a significant impact on the program. Simple mistakes like bouncing or jarring a load, or moving the crane down when it should go up, can damage fragile flight hardware and cause major delays in processing. Hazardous commodities (high pressure gas, hypergolic propellants, and solid rocket motors) can cause life safety concerns for the workers performing the lifting operations. Most crane accidents are preventable with the correct training and understanding of potential hazards. Designing the crane with human factors taken into account can prevent many accidents. Engineers are also responsible for preparing lift plans where understanding the safety issues can prevent or mitigate potential accidents. Cranes are widely used across many areas of KSC. Failure of these cranes often leads to injury, high damage costs, and significant delays in program objectives. Following a basic set of principles and procedures during design, fabrication, testing, regular use, and maintenance can significantly minimize many of these failures. As the accident analysis shows, load drops are often caused or influenced by human factors. Therefore, proper training and understanding of crane safety throughout the workforce is critical. It is important that the engineers designing the cranes, lift planners preparing the lift plans, operators performing the lifts, and training officers conducting the operator training all understand the problems that can happen with cranes and how to ensure the safety of the workforce and equipment being lifted.

Materials Handling↗

Design-Technology Co-Optimization for NVM-based Neuromorphic Processing Elements

An emerging use-case of machine learning (ML) is to train a model on a high-performance system and deploy the trained model on energy-constrained embedded systems. Neuromorphic hardware platforms, which operate on principles of the biological brain, can significantly lower the energy overhead of a machine learning inference task, making these platforms an attractive solution for embedded ML systems. In this paper, we present a design-technology tradeoff analysis to implement such inference tasks on the processing elements (PEs) of a Non-Volatile Memory (NVM)-based neuromorphic hardware. Through detailed circuit-level simulations at scaled process technology nodes, we show the negative impact of technology scaling on the information-processing latency, which impacts the quality-of-service (QoS) of an embedded ML system. At a finer granularity, the latency inside a PE depends on 1) the delay introduced by parasitic components on its current paths, and 2) the varying delay to sense different resistance states of its NVM cells. Based on these two observations, we make the following three contributions. First, on the technology front, we propose an optimization scheme where the NVM resistance state that takes the longest time to sense is set on current paths having the least delay, and vice versa, reducing the average PE latency, which improves the QoS. Second, on the architecture front, we introduce isolation transistors within each PE to partition it into regions that can be individually power-gated, reducing both latency and energy. Finally, on the system-software front, we propose a mechanism to leverage the proposed technological and architectural enhancements when implementing a machine-learning inference task on neuromorphic PEs of the hardware. Evaluations with a recent neuromorphic hardware architecture show that our proposed design-technology co-optimization approach improves both performance and energy efficiency of machine-learning inference tasks without incurring high cost-per-bit.

42 ENGINEERING↗

Protonospheric columnar electron content determination. I - Analysis.

A combination of phase-path length difference and Faraday rotation angle data obtained from geostationary satellite transmissions is used to determine the integration constant necessary to convert phase-path length difference information into absolute values of total slant columnar electron content. The total content thus determined, which is the sum of the ionospheric and protonospheric contents, is measured with uncertainties about one order of magnitude smaller than the value of the protonospheric content. It is thus, in principle, possible to determine the latter by subtracting from the measurement the so-called 'Faraday content.' This idea, proposed by several authors in the past, is critically examined in the present paper. It is impossible to totally eliminate the ionospheric contribution to the measurements; however, it is shown that the degree of elimination depends on the type of distribution of the longitudinal component of the geomagnetic field along the path of observation. Satisfactory minimization of the ionospheric contribution can be accomplished only under certain geometries of observation.

Almeida, O. G.↗

Gas-Granular Simulation Framework for Spacecraft Landing Plume-Surface Interaction and Debris Transport Analysis

The Gas-Granular Flow Solver (GGFS) multi-phase flow computational framework has been developed to enable simulations of particle flows complex extra-terrestrial regolith materials. Particle flows of interest include the damage of unprepared landing sites from rocket plume impingement on Moon, Mars, and asteroids. The flow solver implements an Eulerian-Eulerian two-fluid model with fluid representation of the gas phase and granular phase to avoid the need to model billions of particle interactions. The granular phase is modeled as an Eulerian fluid with constituent physics closure models derived from first-principle Discrete Element Model (DEM) particle interaction simulations that capture the complex, non-linear granular particle interaction effects. Granular phase constituent models have been developed and integrated that address the complex, non-linear granular material mechanics complexities resulting from both: the irregular, jagged particle shapes and poly-disperse mixture effects encountered in extra-terrestrial regolith, with lunar regolith as the extreme. The GGFS capabilities are being integrated into a proven NASA plume-surface interaction and debris transport simulation framework featuring the Loci/CHEM CFD program and Debris Transport Analysis (DTA) post-processing tools for applications in robotic and human Moon and Mars lander development. Integration of the three simulation tool components. Loci/CHEM, GGFS, and DTA, into a coordinated simulation framework will enable time-accurate spacecraft landing simulations that account for the alteration of the landing surface through plume-induced cratering and the resulting redirection of plume impingement flow and debris transport. Initial implementation of this simulation framework and application examples will be presented.

Liever, Peter A.↗

Definitive Mineralogical Analysis of Mars Analog Rocks Using the CheMin XRD/XRF Instrument

Mineral identification is a critical component of Mars Astrobiological missions. Chemical or elemental data alone are not definitive because a single elemental or chemical composition or even a single bonding type can represent a range of substances or mineral assemblages. Minerals are defined as unique structural and compositional phases that occur naturally. There are about 15,000 minerals that have been described on Earth, all uniquely identifiable via diffraction methods. There are likely many minerals yet undiscovered on Earth, and likewise on Mars. If an unknown phase is identified on Mars, it can be fully characterized by structural (X-ray Diffraction, XRD) and elemental analysis (X-ray Fluorescence, XRF) without recourse to other data because XRD relies on the principles of atomic arrangement for its determinations. XRD is the principal means of identification and characterization of minerals on Earth.

Blake, D. F.↗

Hydrogen isotope analysis in W-tiles using fs-LIBS

Abstract Laser-Induced Breakdown Spectroscopy (LIBS) is a promising technology for in-situ analysis of Plasma-Facing Components in magnetic confinement fusion facilities. It is of major interest to monitor the hydrogen isotope retention i.e. tritium and deuterium over many operation hours to guarantee safety and availability of the future reactor. In our studies we use ultraviolet femtosecond laser pulses to analyze tungsten (W) tiles that were exposed to a deuterium plasma in the linear plasma device PSI-2, which mimics conditions at the first wall. A high-resolution spectrometer is used to detect the Balmer- $$\alpha$$ α transition of the surface from implanted hydrogen isotopes (H and D). We use Calibration Free CF-LIBS to quantify the amount of deuterium stored in W. This proof-of-principle study shows the applicability of femtosecond lasers for the detection of low deuterium concentration as present in first wall material of prevailing fusion experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

The Impact of Carotenoid Energy Levels on the Exciton Dynamics and Singlet–Triplet Annihilation in Isolated Bacterial Light-Harvesting 2 Complexes

The light-harvesting 2 (LH2) complex of purple phototrophic bacteria plays a critical role in absorbing solar energy and distributing the excitation energy. Exciton dynamics within LH2 complexes are controlled by the structural arrangement and energy levels of the bacteriochlorophyll (BChl) and carotenoid (Car) pigments. However, there is still debate over the competing light-harvesting versus energy-dissipation pathways. In this work, we compared five variants of the LH2 complex from genetically modified strains of Rhodobacter sphaeroides, all containing the same BChls but different Cars with increasing conjugation: zeta-carotene (N = 7; LH2 Zeta ), neurosporene (N = 9; LH2 Neu ), spheroidene (N = 10; LH2 Spher ), lycopene (N = 11; LH2 Lyco ), and spirilloxanthin (N = 13; LH2 Spir ). Absorption measurements confirmed that the Car excited-state energy decreased with increasing conjugation. Similarly, fluorescence spectra showed that the B850 BChl emission peak had an increasing red shift from LH2 Zeta →(LH2 Neu /LH2 Spher )→LH2 Lyco →LH2 Spir . In contrast, time-resolved fluorescence and ultrafast transient absorption (fs-TA) revealed similar excited-state lifetimes (∼1 ns) for all complexes except LH2 Spir (∼0.7 ns). From fs-TA analysis, an additional ∼7 ps nonradiative dissipation step from B850 BChl was observed for LH2 Zeta . Further, singlet− singlet and singlet−triplet annihilation studies showed a ∼50% average fluorescence lifetime reduction in LH2Zeta at high laser power and high repetition rate, compared to ∼10−15% reductions in LH2 Neu /LH2 Spher /LH2 Lyco and minimal lifetime change in LH2 Spir . In LH2 Zeta , the fastest decay component (<50 ps) became prominent at high repetition rates, consistent with strong singlet−triplet annihilation. Nanosecond TA measurements revealed long-lived (>40 μs) BChl triplet states in LH2 Zeta and signs of damage caused by singlet oxygen, whereas other LH2s showed faster triplet quenching (∼18 ns) by Cars. These findings highlight a key design principle of LH2 complexes: the Car triplet energy must be significantly lower than the BChl triplet energy to efficiently quench BChl triplets that otherwise act as potent “trap states,” causing exciton annihilation in laser-based experiments or photodamage in native membranes.

Absorption↗

Testing the Equivalence Principle in an Einstein Elevator: Detector Dynamics and Gravity Perturbations

We discuss specific, recent advances in the analysis of an experiment to test the Equivalence Principle (EP) in free fall. A differential accelerometer detector with two proof masses of different materials free falls inside an evacuated capsule previously released from a stratospheric balloon. The detector spins slowly about its horizontal axis during the fall. An EP violation signal (if present) will manifest itself at the rotational frequency of the detector. The detector operates in a quiet environment as it slowly moves with respect to the co-moving capsule. There are, however, gravitational and dynamical noise contributions that need to be evaluated in order to define key requirements for this experiment. Specifically, higher-order mass moments of the capsule contribute errors to the differential acceleration output with components at the spin frequency which need to be minimized. The dynamics of the free falling detector (in its present design) has been simulated in order to estimate the tolerable errors at release which, in turn, define the release mechanism requirements. Moreover, the study of the higher-order mass moments for a worst-case position of the detector package relative to the cryostat has led to the definition of requirements on the shape and size of the proof masses.

Hubbard, Dorthy↗

HARMONY: Large-Scale Architecture Search for Efficient Hybrid Language Models

As large language models scale to trillions of parameters, their computational and memory requirements present critical challenges for efficient training and deployment. While Mixture of Experts (MoE) architectures enable efficient scaling through sparse parameter activation, and state-space models like Mamba offer linear-time complexity, principled methods for combining these paradigms remain undeveloped. We introduce HARMONY (Hybrid Architecture Research for Mamba, Optimized with Neural efficiencY), a multi-objective evolutionary neural architecture search framework for discovering efficient hybrid language models that integrate Transformer attention mechanisms, Mixture-of-Experts routing, and Mamba state-space components. Through large-scale distributed search using 16,384 MI250X GPUs on the Frontier supercomputer, HARMONY explores a comprehensive design space encompassing six attention variants (MHA, MQA, GQA, MLA, SWA, and Mamba-2), variable MoE configurations with both routed and shared experts, and extensive Mamba hyperparameters. Our framework discovers heterogeneous architectures that balance training performance with computational efficiency through multi-objective optimization incorporating latency penalties and fitness-based selection. Analysis of discovered architectures reveals that optimal hybrid designs favor heterogeneous component mixing rather than homogeneous patterns, with Mamba-2 and Multi-Head Latent Attention (MLA) emerging as preferred mechanisms. Discovered architectures demonstrate superior training efficiency: our best configuration achieves a final perplexity of 1.0874 with 2.38B parameters while processing 4,320 tokens/second, outperforming significantly larger manually designed models. Full-scale evaluation shows HARMONY's top architectures achieve better loss trajectories than equivalently-sized models using state-of-the-art configurations including Mixtral, Jamba, and Samba. Additionally, we demonstrate 91% weak scaling efficiency when training discovered 36B-parameter models across 1,024 GPUs. HARMONY is released as an open framework with comprehensive tools for building and training hybrid models using expert-data-pipeline parallelism, democratizing access to automated architecture design for next-generation language models.

Herron, Emily [ORNL] (ORCID:0000000273008172)↗

Analysis of effective thermal conductivity of fibrous materials

The objective of this research is to gain a better understanding of the various mechanisms of heat transfer through fibrous materials and to gain insight into how fill-gas pressure influences the effective thermal conductivity. By way of first principles and some empiricism, two mathematical models are constructed to correlate experimental data. The data are obtained from a test series measuring the effective thermal conductivity of Nomex using a two-sided guarded hot-plate heater apparatus. Tests are conducted for certain mean temperatures and fill-gases over a range of pressures varying from vacuum to atmospheric conditions. The models are then evaluated to determine their effectiveness in representing the effective thermal conductivity of a fibrous material. The models presented herein predict the effective thermal conductivity of Nomex extremely well. Since the influence of gas conduction is determined to be the most influential component in predicting the effective thermal conductivity of a fibrous material, an improved representation of gas conduction is developed. Finally, some recommendations for extension to other random-oriented fiber materials are made concerning the usefulness of each model depending on their advantages and disadvantages.

Futschik, Michael W.↗